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I 



APRIL 1985 VOL.10, NO. 4 



$3.50 m UNITED STATES 

$4.25 IN CANADA / £2.10 IN U.K. 

A McGRAW-HILL PUBLICATION 

0360-5280 



THE SMALL SYSTEMS JOUR' 



ARTIFICIAL 
INTELLIGENCE 



Introducing The 
AHyou rave fe 






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CONTENTS 




100 




124 



FEATURES 



Introduction 100 

Ciarcia's Circuit Cellar: Build the Home Run Control System. 

Part I: Introduction by Steve Garcia 102 

Steve returns to the field of home control in this first part of a three-part series. 

Coprocessing in Modula-2 by Colleen Roe Wilson 113 

This method lets you cooperatively process information by interleaved 
execution on a single computer. 

A Million-Point Graphics Tablet by lames Hawley 120 

Build a graphics pad for less than $200 using the KoalaPad for input. 

THEMES 



Introduction . 124 

Communication with Alien Intelligence by Marvin Minsky 126 

It may not be as difficult as you would think 

The Quest to Understand Thinking 

by Roger Sehank and Larry Hunter 143 

It begins not with complex issues but with the most trivial of processes. 

The LISP Tutor by \ohn R. Anderson and Brian |. Reiser 159 

The system described offers many of the advantages of a human tutor 
in teaching LISP programming 

PROUST by W. lewis \ohnson and Elliot Soloway 179 

This LISP program automatically debugs the efforts of novice Pascal programmers 

Architectures for AI by Michael F. Deering 193 

The right combination of hardware and software is necessary for 
efficient processing. 

The LISP Revolution by Patrick H. Winston 209 

The language is no longer limited to -a lucky few. 

The Challenge of Open Systems by Carl Hewitt 223 

Current logic programming methods may be insufficient for developing the 

intelligent systems of the future. 

Vision by Dana H. Ballard and Christopher M. Brown 245 

Technology is still being challenged to create reliable real-time vision systems. 

Learning in Parallel Networks by Geoffrey E. Hinton 265 

The author presents two theories of how learning could occur 
in brain-like networks. 

Connections by lerome A. Eeldman 277 

Massively parallel computational models may simulate intelligent behavior more 
closely than models based on sequential machines. 

Reverse Engineering the Brain by lohn K. Stevens 286 

The brain's circuitry can serve as a model for silicon-based designs. 

The Technology of Expert Systems 

by Robert H. Michaelsen, Donald Michie. and Albert Boulanger 303 

There's more than one way to transplant expert knowledge to machines. 

Inside an Expert System by Beverly A. Thompson and William A. Thompson 315 

The authors trace the development of a rule-based system from index cards 
to a Pascal program. 



BY 1 L MSS\ 0160 VWi is published monthly by McGraw-Hill inc Founder lames H McCraw (I860- 1448) Executive editorial circulation and advents- 

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2 BYTE' APRIL 1985 



COVER ILLUSTRATION BY ROBERT TINNEY 



VOLUME 10. NUMBER 4. 1985 



REVIEWS 



Introduction 334 

Reviewers Notebook by Glenn Hartwig 337 

The ITT XTRA by ]ohn D. Vnger 338 

An IBM PC-compatible system with telecommunications software. 

Insight- A Knowledge System by Bruce D'Ambrosio 345 

Software to help you build an expert system and learn about artificial 
intelligence. 

Review Feedback 348 

Readers respond to previous reviews. 

KERNEL 



Introduction 353 

Computing at Chaos Manor: Over the Moat by jerry Pournelle 355 

As construction workers descend on Chaos Manor, jerry battles the flu 
to look at more new items. 

Chaos Manor Mail conducted by \erry Pournelle 373 

Jerry's readers write, and he replies. 

BYTE West Coast Lasers. Office Publishing, and More by John Markoff and 

Phillip Robinson 379 

Our West Coast editors report on Interleaf's OPS2000 and TPS-2000 and 
on FastFinder for the Macintosh. 

BYTE U.K.: New Database Ideas by Dick Pountain 389 

I.D.E.A.S. is a commercial database-generator package in which all data items 
are related by a system of coordinates abstracted from the real world. 

BYTE Japan: The Fifth Generation in Japan by William M. Raike 401 

Our Japan correspondent takes note of the International Conference 
of Fifth Generation Computer Systems, the new Hitachi supercomputer, 
and software development in the country. 

Circuit Cellar Feedback conducted by Stew Garcia 408 

Steve answers project-related queries from readers. 




334 



EDITORIAL: GOLFERS AND HACKERS 6 

MlCROBYTES 9 

Letters 14 

Fixes and Updates 33 

Whats New 39, 440 

Ask BYTE 48 

Clubs & Newsletters 58 

Book Reviews 65 



Event Queue 83 

Whats Not 96 

Books Received 414 

Programming Insight 429 

Unclassified Ads 493 

BYTE's Ongoing Monitor Box. 
BOMB Results 494 

Reader Service 495 




353 



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SECTION ART BY DOUGLAS SMITH 



APRIL 1985 • BYTE 



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lilTE 



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Philip Lemmons 
managing editor 
Gene Smarte 
consulting editors 

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ierry pournelle 

senior technical editors 

G Michael Vose, Themes 
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electronic publishing and communications 

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user news editor. east coast 

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USER NEWS EDITOR, WEST COAST 

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CONTRIBUTING EDITORS 

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II 




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Inquiry 97 



APRIL 1985 'BYTE 5 



EDITORIAL 



Golfers and Hackers 

It must no longer go unremarked that 
many of the criminals who threaten 
the foundations of our society are 
golfers. Golfers persist in attacking our 
personal, financial, and military 
security Many golfers, like the famous 
one caught in the act in photo 1 (Spiro 
Agnew), have been involved in extor- 
tion, bribery, or other forms of 
corruption. 

Some golfers have been known to 
hit out of bounds as a pretext for 
trespassing in residential communi- 
ties. Such forays easily turn into in- 
cidents of voyeurism and burglary. 

Violence 

Other golfers use the harmless-look- 
ing little white balls to inflict injuries 
on bystanders, propelling the danger- 
ous projectiles at speeds in excess of 
120 miles per hour. The danger of 
head injuries is obvious. Golf's care- 
less disregard for the safety of other 
people hardens our children to vio- 
lence. The idea that shouting a single, 
obscure word makes it all right to bop 
some innocent person on the head 
with a hard projectile has brought our 
society to the brink of savagery. Last 
week in a major American city a thug 
shouted "Fore!" and then mugged a 
grandmother as if it were the most 
natural thing in the world. 

Golfing Arcades 

Perhaps the most distasteful thing 
about golfers is their use in recent 
years of golfing arcades. These so- 
called "driving ranges" allow addicts 
to rent baskets containing dozens or 
even hundreds of golf balls so that the 
addicts can bombard surrounding 
land at rates previously unthinkable. 
Although the fences sometimes used 
around these golfing dens may pro- 
tect people outside from physical in- 




ife^ . 




jury the fences do nothing to stop the 
spread of the moral rot associated 
with the trancelike concentration of 
the golfer on the little white ball. That 
little ball means more to the golf ad- 
dict than honor, mother, or country. 
The money squandered at golfing 
arcades, golf courses, and pro shops 
could buy a personal computer for 
every child in America or pay off the 
national debt, depending on national 
priorities. 

National Security 
Implications 

The parliament of King lames II of 
1457 banned golf because its addicts 
neglected to practice the use of the 
crossbow, then the chief means of na- 
tional defense. Today in this country 
golfers neglect the most advanced 
weapons systems in history. This 
neglect could nullify all the technical 
progress recently seen in weapons 
research. What good is an orbital- 
beam weapon if the operator is busy 
selecting a club? 

It doesn't take a genius to see that 
avoidance of golf is a cornerstone of 
Soviet military strategy. This gives the 
Soviets a tremendous advantage in 
daytime warfare. If the Soviets launch 
an attack at 3 p.m. EST on a weekday 
in June, approximately 20 percent of 
American manpower will be useless- 
ly deployed in fairways, sandtraps, 



and rough. Even those in bunkers will 
be in the wrong kind of bunkers. At 
3 p.m. on a weekend, as much as 50 
percent of our manpower might be 
trying to avoid bogies rather than to 
shoot them down. 

Call to Action 

Because of the threats that golfers 
pose to national security and our 
moral fiber, we are proposing that all 
golfers be arrested as soon as 
possible. 

Unfair? 

If the foregoing attack on golfers 
seems unfair (and, of course, the anal- 
ogy is not perfect), it is little more so 
than the attack in the general press 
on hackers of another kind— comput- 
er hackers. Some national publica- 
tions have used the term "hacker" in- 
correctly as a synonym for "criminal." 
Hackers are people who play with 
computers at a technical level be- 
cause they enjoy doing so. There are 
many thousands of hackers in North 
America. A few hackers use their com- 
puter skills for pranks, and fewer still 
use their skills to commit crimes. But 
the chances are excellent that far 
more hackers are helping build 
defenses around databases than try- 
ing to penetrate them. If even one 
percent of hackers started trying to in- 
vade our databases, problems would 
be far more serious than those sen- 
sationalized in the general press. 

It wasn't being a golfer that got 
Spiro Agnew into trouble. Just being 
a hacker won't get anyone into trou- 
ble, either. Hackers are as entitled to 
the presumption of innocence as 
golfers and other common special- 
interest groups. Hackers are also en- 
titled to the continued correct use of 
the authentic, distinctive and color- 
ful name that they gave themselves. 
—Phil Lemmons, Editor in Chief 



5YTE • APRIL 1985 



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APRIL 1985 -BYTE 7 



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(609) 683-1660. Telex. 821402 PGS PRIN. (800) 221-1490 Ext 204 



IBM PC, PC XT, and PC AT are registered trademarks o! International Business Machines, Inc. 



8 BYTE 



APRIL I985 



Inquiry 4I3 



MICROBYTES 



Staff-written highlights of late developments in the microcomputer industry. 



Macintosh Users Get IBM PC Emulator 

Dayna Communications, Salt Lake City, UT, has announced MacCharlie, a hardware-and- 
software system that allows Macintosh users to run IBM PC software. Two hardware com- 
ponents are included: one adds 10 function keys and an 18-key numeric keypad/cursor pad 
to the Macintosh keyboard; the other has one or two 5 '/4-inch disk drives, memory, an IBM- 
compatible ROM chip, and an 8088 processor, as well as serial and parallel ports and a 
bus-extender port for an optional expansion chassis. Also included is a Macintosh program 
that handles all keyboard and display processing— and it can still be used to access the 
Mac's desk accessories from within IBM PC applications, MacCharlie emulates all features of 
the IBM monochrome graphics card except for light-pen support. 

The Macintosh can be set atop the matching MacCharlie unit, which adds four inches to 
the Macintosh's width and one inch to its height. The Macintosh keyboard fits into the 
keyboard extender; the numeric keypad can be used as a standard Macintosh numeric 
keypad when in Macintosh mode. The bus-extender port allows use of an optional expan- 
sion chassis so that IBM cards can be installed; with an additional cable, IBM's expansion 
chassis can be used. With one 5 '/4-inch disk drive and 256K bytes of memory, MacCharlie is 
$1195; with two drives and 640K, it's $1895. 

New Mac Products Shown 

Several companies unveiled new products for the Macintosh at the MacWorld Expo in San 
Francisco. While many new software titles were demonstrated, memory-expansion and hard- 
disk-drive exhibits drew much attention. 

Micro Conversion, Arlington, TX, and Levco Enterprises, Del Mar, CA, both offer complete 
512K-byte upgrades for $400, including installation, and also sell uninstalled kits. Levco also 
sells a $60 kit with all necessary parts except the 2 56K-byte chips. 

In addition to already-announced hard-disk products, new drives from Paradise Systems 
Inc. and Micro-Design were shown in prototype form. Not surprisingly, most exhibitors used 
hard disks and 512K-byte Macs to demonstrate their software. 

Hayden Software showed Ensemble, an integrated package for the 128K-byte Mac. Data- 
base, spreadsheet, graphics, and text-processing features are included in the $300 program, 
which was developed in France. A number of new database programs were also exhibited 
at the show. 

Paragon Courseware, Del Mar, CA, offers two font sets: a $50 Scientific Typing font and a 
$100 Electronic Circuits font. 

Micro Focus Inc. now offers MacCOBOL, a COBOL development system. 

Microsoft Releases Its Own C Compiler 

Microsoft has released Microsoft C version 3.0, which replaces the Lattice-developed C 
previously sold by Microsoft for the IBM PC. Microsoft's C compiler provides file-sharing 
and record-locking features for use in network environments; a separate Windows Toolkit 
will help C programmers develop applications to run under Microsoft Windows. Microsoft 
says that source and object code can be linked to run directly under MS-DOS or XENIX 
without modification. Microsoft C is $395. 

New LCD Portables Use Backlit Display 

Zenith Data Systems is expected to introduce a lap-top portable computer with a backlit 
liquid-crystal display (LCD). The 16-pound Z-175 will include one or two 5!4-inch disk drives, 
256K bytes of RAM, and an 80C88 processor for less than $3000. 

To counter the viewing angle and lighting problems caused by LCDs, Morrow Design also 
changed the 16-line by 80-character display on its Pivot computer, switching to backlit LCDs 
rather than relying on room light, despite the extra power consumed by the backlighting. 



{continued} 
APRIL 1985 'BYTE 9 



Proteon Adds 80-megabit-per-second Network 

Proteon, which markets the ProNET token-passing star/ring hybrid local-area network, now 
offers a faster network. While ProNET used a 10-megabit-per-second data rate, ProNET-80 
transfers information at 80 megabits per second. Proteon expects it to be used in applica- 
tions using multiple minicomputers and mainframes or in connecting graphics workstations 
with large file sizes. The network will be available for Unibus and Multibus systems for 
about $8000 per node. 

Fntel Will Sell CalTeeh's Hypercube Multiprocessor Computer 

Intel has licensed the hypercube computer design from the California Institute of 
Technology and will sell a computer based on that multiprocessor architecture. The com- 
puter consists of a multiprocessor cube and a cube manager. The cube includes 32, 64, or 
128 computational nodes, each of which includes an 80286 processor, an 80287 math 
coprocessor, and 512K bytes of memory. Each node in the cube can communicate with five 
adjacent nodes and with the cube manager through 10-megabit-per-second communications 
channels. The cube manager is an Intel 286/310 microcomputer with 2 megabytes of RAM 
and a 40-megabyte hard-disk drive. Intel claims a performance range from 2.5 to 10 million 
floating-point operations per second with an efficiency of 80 to 99 percent. Prices range 
from $150,000 to $520,000. 

Torus Prepares to Launch LAN Software 

Torus Systems Inc., Redwood City. CA, plans to introduce icon-based user-interface software 
for IBM PC network environments this month. The product will be based on Icon, the net- 
work software it says it has been selling since July in England for systems using 3Coms 
Ethernet network cards. 

The program will include intranetwork electronic mail, telecommunications, file locking and 
sharing, and other network software features; users will also be able to run standard MS- 
DOS programs under the environment, either from local disks or from a file server. 

NANOBYTES 



While announcing the Macintosh Office in late January (see February BYTE, page 120), 
Apple also announced the Macintosh XL, which is simply the Lisa renamed. . . . Software 
Publishing Corporation has added XMODEM file-transfer and remote computer access 
features to its $140 pfs:Access program. . . . Kensington Microware, which advertised its 
Quick Cursor and Printer Buffer for Apples Macintosh last year, has canceled development 
of those products. The company will continue to sell other "Maccessories. ". , . Mostek, 
Toshiba, Hitachi, and AT&T's Bell Labs presented papers on CMOS 1 -megabit RAM chips 
at the International Solid State Circuits Conference (1SSCC) in February; IBM, NEC 
Mitsubishi, Toshiba, and Fujitsu discussed NMOS I-megabit RAMs. Image-sensor chips 
were discussed by Mitsubishi and Sharp, and engineers from AT&T's Bell Labs discussed 
the development of a 32-bit floating-point digital-signal-processing chip. . . . Mother Jones' 
Son's Software, Reno, NV, is selling M), a set of background utility programs. In addition to 
redefining the PC's keys, MJ expands the IBM's keyboard buffer from 16 to 1000 keys, 
permits the cursor speed to be changed, and includes a password protection option. M) 
costs $30, or $70. including source code. . . . Digital Equipment Corporation acknowledged 
in February that it had stopped manufacturing the Rainbow personal computer but said it 
will continue to ship from inventory and plans to announce a new version later this year. . . . 
Syntech, Canoga Park, CA, has announced a MIDI (musical instrument digital interface) 
adapter card for IBM, Apple, and Commodore computers. For the Apple or Commodore, 
the card is $100; for the IBM PC, it's $195. . . . The Library Corporation, Washington, DC, is 
selling a complete CD ROM system for the IBM PC, including a disc with records for a 
million English-language books, for $2930. . . . Corvus Systems Inc., San Jose, CA, has 
replaced its line of Omnidrive hard-disk drives with a single model that can be used with 
IBM PC; Apple II, III, and Macintosh; DEC Rainbow; and Zenith Z-100 computers. Corvus 
also dropped prices by about 30 percent. An Il-megabyte drive is now $1995. . . . Hammer 
Computer Systems Inc., Larkspur, CA, announced E-Z-DOS-IT, a $200 program that allows 

up to eight MS-DOS programs to execute concurrently Gold Hill Computers has 

enhanced its Golden Common LISP interpreter and will also offer a GC LISP compiler in 
the summer. A large-memory-model version will also be available for the IBM PC AT. 



10 B YTE • APRIL 1985 



TheTI855is 

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APRIL 1985 • BYTE 



interact with a Genius 




SUPER XT SYSTEM PLUS* 

Ultra-High resolution color card. 

Ultra-High (720x400) resolution color monitor. 

Gives excellent text resolution. 

10x16 character cell. 

SUPER XT OFFICE SYSTEM PLUS® 

TTL monochrome monitor. 

Gives you easy-on-the-eyes viewing. 



SUPER XT COLOR SYSTEM PLUS® 

High resolution color card and color monitor (640x200). 
16 colors. 

SUPER XT STRRTER SYSTEM PLUS® 

Composite monochrome monitor. 

Includes color graphics card. 

Gives you flexibility to run color and monochrome 

software. 





12 



B YTE • APRIL 1985 



Inquiry 417 for Dealers. Inquiry 418 for End Users. 



... and feel the Power! 



SUPERPOWER 135 

Hard Disk ready +12V at 
4.5A max +5V at ISA max 
Same dimension and plug 
compatible W/IBM PC/XT. 
3 Power outputs for 2 
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KEYBOARD 

IBM PC ; XT Plug 

compatible 

Corrected (left) 'shift" 

key 

Color compatible 

W/IBM case 



SUPER 
MOTHERBOARD 

Single layer double 

sided board 

Same dimensions as IBM 

motherboard 

Up to 256K Ram on-board 

memory 

8 I/O slots 



MULTIFUNCTION 
CARD 

Serial, Parallel, Game ports 
and Clock/Calendar 
W/memory expansion of 
added 384K 

RAM disk and print spooler 
software included 



1AXAN 555' 
COLOR CARD 

10x16 character cell to give 
the best text resolution in 
color (720x400) 
Graphic resolution 
(640x200) 
Operates Taxan 440" 
monitor 





\\ ■ , 




SUPER 
CONTROLLER 

Controls up to 4 Floppy 
drives Comes W/Cables 
for 2 Drives 










SUPER DISK 
+ 1/0 

Disk Controller Parallel 
Serial ports 
Saves a slot in 
Motherboard 



SUPERSEVEN + 

Disk Controller and cable 
Clock/calendar Parallel, 
Serial and Game ports. 
RAM Disk emulator. 
Super Spooler software 



SUPERBUFFER + 

Does not use User's 
memory. Can be used as 
regular printer port W/O 
64K buffer memory 
installed. 

Second parallel port 
included. Configurable as 
LPT1 or LPT2. Use 
Computer and print 
at the same time 

SUFERCOLOR 
CARD 

16 Colors on medium 

resolution 

16K display memory 

Composite output 

W/RGB 








SUPERBOX 

Fully BUS compatible 

Adds 10 slots. 135 W Power 

supply for Hard Disk and 

Add-Ons 

External color same as IBM 




HARD DISK 
CONTROLLER 

Controls up to 2 hard disks 
Configurable for 5, 10, 20 
and 33 Mb hard disks 




HARD DISK 
ASSEMBDT 

10 Mb formatted Fixed disk 
5 Mb or 10 Mb formatted 
removable cartridge 
Unlimited storage 
Bootable from either fixed 
or removable hard disk 



TAPE BACKUP 

Backs up 10 Mb within 3 

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Uses regular floppy 

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SUPERMONO 
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720x348 resolution 
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Printer port 




The Ultimate in PC/XT compatibles and peripherals! 



The Super XT Plus Series" computer offers 
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Standard features on all Super XT Pins 
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IBM PC/XT is a registered trademark of International Business Machines, Corp. Taxan is a registered trademark of Taxan Corp 



SEE US AT COMDEX-LOS ANGELES 



* 1985 Supercomputer, Inc 

DEALER AND OEM INQUIRES INVITED 

FAX 213/532-6342 
TELEX 3719484 SUPER 

Super XT System Plus; Color System Plus; Office System Plus; and Starter 
System Plus are registered trademarks of Super Computer, Inc. 

APRIL 1985 'BYTE 13 



LETTERS 



Covering Advanced Systems 

I have now been using a Fujitsu Micro 1 6s 
(8086 processor) for the past eight 
months, and I don't know how I got this 
far without some kind of micro, I am 
already planning for my next system. 
which will have either a 68020, a 16032, 
or a 32032 processor running UNIX. 

Along with Jay Steinbrunn (Letters, 
August 1984, page 23}, I too would like 
to see BYTE raise its sights and start to 
cover this future marketplace. Tell us 
what's happening out there so I can start 
putting money into my "purchase" ac- 
count. I've seen a few inklings of this ad- 
vanced micro technology at some of the 
shows, namely Saber Technology's use of 
the NS32032. 

There are probably more of us out there 
that are interested in these advanced 
systems than you realize. 

William H. Mestler 
Tarzana, CA 

Phil Lemmons replies: 

We will keep an eye out for real 32-bit 

microcomputers at reasonable prices. 

An Apple for BYTE 

1 want to compliment you on your special 
articles on the Apple computers (The BYTE 
Guide to the Apple Personal Computers, 
December 1984). The length of the articles 
showed that your company spent many 
hours choosing articles that would be en- 
joyed by the majority of readers. The ar- 
ticles were not only enjoyable, but they 
were also very informative. They showed 
an extreme amount of quality, which was 
the biggest impression I had after reading 
them. I commend your writers and com- 
pany on a job well done. 

Kevin Hoekman 
Lakewood. CA 

Where Credit Is Due 

I have just read your December 1984 
issue. I was impressed by "High-Speed 
Dial-up Modems'' by Kim Maxwell (page 
179). I found the article very informative 
and timely. Kim Maxwell's writing style is 
always very informative. He also manages 



to keep the reader interested throughout 
any articles he writes. 

But I must challenge the description of 
Mr, Maxwell's accomplishments. Mr. Max- 
well is the current president of Racal-Vadic 
He also holds a philosophy degree from 
Stanford. The remainder of the descrip- 
tion is not correct. 

Racal-Vadic was founded in April 1969 
by seven individuals: Ted Saunders, Bob 
Stires, Jay Tiitt, Tom McShane, Jim Barrick, 
Larry Taylor, and Kim Maxwell. The com- 
pany was then known as Vadic. The ideas 
and circuits used to start Vadic were Ted 
Saunders's. 

The very first full-duplex 1200-bps 
modem was invented and designed by 
lohn A. C. Bingham in 1972 during his 
employment at Vadic, Bingham must be 
given credit where credit is due. Mr. 
Bingham's talents and contributions need 
to be recognized. 

This is not meant to take anything away 
from Kim Maxwell. It is just to set the 
record straight. Mr. Maxwell's contribu- 
tions to the world of data communications 
are numerous, too numerous to list. He 
has peers in this group, but very few. 

An an engineer and investor at Vadic 
from November 1969 to November 1984, 
1 saw most of the events during that period 
and was party to many. I also worked for 
both men and admire their talents and 
contributions to data communications. 

DUANE MARCROFT 

San Carlos, CA 

WordStar s .BAK 
Extension 

I read Vincent Alfieri's "WordStar as a Pro- 
gramming Tool" (November 1984, page 
505) with some enjoyment. 1 have long 
used WordStar for both program develop- 
ment and correspondence, and I agree 
with Dr. Alfieri's verdict that it is a program 
hard to beat in power and versatility. Even 
after several years of using WordStar, in- 
cluding writing patches and modifications 
to the program itself, it still manages to 
surprise me with its power. 

1 know that the problem that Dr. Alfieri 
has experienced with limited disk space 
is frustrating; I used to have the same 
problem myself. While my ultimate solu- 



tion was to move to 8-inch disks, there are 
more immediately applicable fixes. The 
problem stems from the fact that Word- 
Star saves the old version of an edited file. 
changing the file extension to .BAK, Hav- 
ing rescued program files from otherwise 
hopeless oblivion by the use of this fea- 
ture, 1 am quite willing to put up with its 
rather extravagant use of disk space. 

It is an almost undocumented feature of 
WordStar that allows you to specify a disk 
drive to receive all work files and the final 
edited file other than the drive on which 
the original file resides. This can be done 
in either of two ways. From the Opening 
Menu, simply choose "D" or "N," as ap- 
propriate, and when asked for the name 
of the file to edit, reply with the filename, 
but follow it with a space and a drive 
designator. For example, to edit the file 
TEST. DOC, which resides on drive B:, and 
save the final, edited version on drive A:, 
answer the "Name of file to edit?" ques- 
tion with BTEST.DOC A:. When you end 
the editing session, you will be left with 
the file TEST. BAK on drive B:, and the file 
TESTDOC on drive A:. For subsequent 
editing, it will be necessary to use drive 
A: as the source drive and B: as the 
destination. The second way to invoke this 
feature is from the CP/M (or MS-DOS) 
command line. To accomplish the same 
task using this method, simply type WS 
BTEST.DOC A: at the A> operating- 
system prompt. You can change the mode 
(document or nondocument) to which 
WordStar will default using this method by 
using WINSTALL.COM. 

If this still leaves you with insufficient 
room on the A: drive, WordStar can be run 
without the file WSMSGS.OVR on the 

{continued) 



LETTERS POLICY: To be considered for pub- 
lication, a letter must be typed double-spaced on 
one side of the paper and must include your name 
and address. Comments and ideas should be ex- 
pressed as clearly and concisely as possible. 
Listings and tables may be printed along with 
a letter if they are short and legible. 

Because BYTE receives hundreds of letters each 
month, not all of them can be published, letters 
will not be returned to authors. Generally it takes 
four months from the time BYTE receives a let- 
ter until it is published. 



14 



B YTE • APRIL 1985 




Hard Drives 



You Can Forget About 





The nicest thing about May nard's hard drives is their 
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nind on your work, not your hardware. Unsurpassed 
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/ou an awful lot to forget about. 





Internal, external, or portable 
hard drives from 10 to 30MB. 




Maynard Electronics 

430 E. SEMORAN BLVD., CASSELBERRY, FL 32707 
305/331-6402 

Inquiry 253 



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COD 



LETTERS 



system disk. All messages, including 
menus, will appear as @@@@ in the up- 
per left-hand corner of the screen, but if 
you have sufficient knowledge of Word- 
Star's command structure, that shouldn't 
be more than an inconvenience. 

As I mentioned, this feature is not well 
documented and, I must admit, it is of 
limited usefulness, except in certain situa- 
tions when it makes the impossible 
possible, 

Nick Burkitt 
Long Beach, CA 

As someone who uses WordStar profes- 
sionally on nearly a daily basis, both at 
work (as a technical writer) and at home 
(as a freelance writer), I was flabbergasted 
at several pieces of misinformation and 
bad advice offered by Dr. Vincent Alfieri 
in 'WordStar as a Programming Tool." 

Late in the article, Dr. Alfieri describes 
WordStar's "strange habit of keeping a 
backup file every time you edit an existing 
file. This means, in effect, that you must 
maintain a great deal of disk space for the 
necessary backup files." 

So backup files (denoted by the .BAK 
extension) are bad, since they eat up disk 
space. Or are they? 

Dr. Al fieri 's attitude toward the WordStar 
backup procedure is perplexing, espe- 
cially since one can justify WordStar's 
backup procedure by simply providing a 
better solution to a problem "solved" by 
Dr. Alfieri early on in the article. There, he 
recommends that, if you have recently 
saved and accidentally delete an impor- 
tant line of code, you can use the "KQ 
(quit without saving file) command. He is 
silent on what to do if you haven't, which 
is frequently the case if you are on a roll. 

However, thanks to WordStar's backup 
procedure, the situation isn't bad at all, 
even if you've got an hour's work behind 
you in the current file with no saves at all. 
All you really have to do is use ~ KD (quit 
and save file). Following this, you will find 
that WordStar has created a file with a 
BAK extension on the disk. 

You can then edit this file (after chang- 
ing or removing the .BAK extension). This 
allows you to find the missing text and 
block write it to disk. You can then reedit 
the original file, find the location of the 
missing text, and read it off the disk. This 
procedure is quick, easy, and involves no 
loss of text. 

But even WordStar with its powerful 
backup feature cannot defeat those who 
work to defeat it, as Dr. Alfieri does when 
he suggests using files distinguished solely 

[continued} 



16 B YTE • APRIL 1985 



Inquiry 150 



ProModem 1200... HOT* LI ME 



Our ProModem 1200 Makes 
Smart Modems Look Dumb 




ProModem 1200 

(RS-232) 



Send Or Receive 50 Pages Of Text 
Without Tying Up Your Computer 



COMPUTER 
TURNED OFF 




No wonder Smart Modems, Cats, and Maxwells 
cringe when compared to our $495 ProModem 
1200, an expandable 1200/300 baud modem 
for use with all personal computers. It costs 
less, but is smarter than the rest. 

And when you add our $99 Communica- 
tions Buffer and Alphanumeric Display options, 
ProModem 1200 becomes a veritable genius! 

Imagine, you unplug your computer, take it 
home for the weekend, and while you're gone, 
ProModem 1200 answers the phone, collects 
messages up to 50 pages long, sends out 
electronic mail, and displays all events with the 
exact time of each. Thanks to ProModem 1200, 
expensive, hard-to-use communications soft- 
ware isn't needed. The communications is in the 
modem, and electronic mail becomes aback- 
ground function, where it belongs. 

A 



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Our Communications Buffer is a 4 by 6 card that 
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ProModem 1200 contains a battery backed-up real-time 

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APRIL 1985 "BYTE 17 



Inquiry 135 



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LETTERS 



in terms of extensions (he suggests "P.I." 
"P.2." "P.3." etc.). Yes. in this case WordStar 
will keep only one backup for each of 
those files. That's great, if you're sure you'll 
never need a backup of any but the most 
recently edited file. I, for one, am not so 
confident. 

Obviously. I think there are good 
reasons for backup files. Dr. Alfieri 
reminds us to keep separate backup files, 
but I know from nearly 10 years of work- 
ing with computers and six years of work- 
ing with WordStar that most people forget 
to back up their work, especially if they 
haven't lost any work lately. We WordStar 
users tend to be less sorry than most. 

Finally, I am puzzled by Dr. Alfieri's con- 
tention that "You can actually get more 
pages on a disk with many small files than 
with one large file." This isn't entirely true, 
of course, except during an actual editing 
session. 

Every file has overhead, and many sys- 
tems allocate disk space in 2K-byte in- 
crements, including a minimum 2K-byte 
file size. Thus, it's easy to eat up disk space 
by having numerous files with somewhere 
between a few bytes and 2K bytes of un- 
used bytes per file Let's say that it's IK 
byte on the average. 

Then, if you take our example l80K-byte 
disk again and put 30 files of nominally 
4K bytes each on it, it adds up to 120K 
bytes used' and 60 K bytes "free." The 
truth, however, is that about 30K bytes of 
disk space is eaten up in overhead. That's 
about 15 pages of text! If your system 
allocates in lK-byte increments, that's still 
I5K bytes! 

When you're editing a backed-up file. 
WordStar can require about three times 
the capacity of the file on the disk (one 
old backup, one working backup, and the 
file being edited). This means that on a 
disk with I80K bytes (formatted), you 
might want to avoid editing a file of 55K 
bytes or greater, especially if you expect 
to be expanding it by much. 

The best solution is probably to work 
on one disk and keep a separate disk for 
file saves. If you save to this disk after each 
edit, then you can delete the .BAK files 
as you go. meaning that on a 180K-byte 
disk, you can safely edit a much larger file 
of 80K bytes or more. 

Thomas H. Hunscher 
Tigard, OR 

News for Sorcerer Owners 

May I suggest that BYTE try to mention 
the many orphans that have arisen in the 

[continued] 



18 BYTE • APRIL 1985 



Inquiry 220 



AST makes modems Short 'n Sweet 



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The Reach! half-card design 
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So it makes a much nicer travel- 
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BYTE 



10 



Quick doesrit have to 

Before Microsoft Word you had to choose between 
quick and clean. Producing professional looking docu- 
ments meant going through draft after draft after draft 
after draft. 

The new Microsoft Word is different. You don't have 
to practice to make perfect. You can use the full power 
of the IBM" PC to eliminate the drafts. And give your ideas 
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With Word, what you see on the screen is what you'll see on the page. 
You can preview and design documents. And instantly see the effect 
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and the printer.) Now you can breathe vitality into blocks of lifeless text. 




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>uty ('man span bathtub b»xd»s? 

■/acwJNI divajr» for laying und*rvatar oa»l« 
Aimmmiit-lma or tmti a* a j»ar»an*nt tr-*" J 




titov-tomkter r l»-< 



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Attachaa to chair a or dining- 



^{1} J*vai2aJbl# i» *&•#**•* and "after" vara ion*; plmmmm «peclf4« 
£#£/ M*U*ftl« In mvky Mountain or Alpina atyia. 



<£^p0«j*M>' -^ 



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TOO TAU. TOYS 
NEW PRODUCTS 



ci.mh.fift Sis* K««t 



const* ueritm cha«k 

«*f«« *eec**wry for aft* Too T«<7 skyscraper 
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an be »r«at»i«iOTe<S to (serfo»t» a vmtiety eC 



* cftwpiex 



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kit ha* » i«id«, , ! " f *** ** sla * 

Z a * ** ** •"* •» • *«««* tea* 



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^T*rZS WUh *° ***»*■ ******* - 

chairs or di»m*-r«o«> wtottt whJ| ^^ 



tattgattw in "faster** Mi -I**" *«MSi™ 



Their first draft vs. our first draft. 



20 BYTE* APRIL 1985 



be dirty* 




Highlight pithy 
phrases, flag impor- 
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superscript an j sahsaipt Qyj Q more hieroglyphic ▼Todes.) 

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How do we get higher performance out of the PC? Simple, our 
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So, if you want to clean up your act, act quick. Call (800) 426-9400. 
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purchased on or before August 31. 19^. 




LETTERS 



computer field. There are many micros 
that have no support now. and users who 
still have them are looking for help. 

Ah, nostalgia! Remember Superbrain, 
TRS Model 1, IMSAI, Videobrain, and 
Exidy Sorcerer 9 Some people still have 
them but think they are frozen in time. 

For some machines, that is not so. 

The Exidy Sorcerer was still being made 
in 1984, under license in Holland. And 
there are still many fan magazines with 
software and hardware notes being 
published. 

For the Exidy Sorcerer here are some 
of the magazines being published. (Write 
for subscription rates and possibility of 
back issues.) 

European Sorcerer Club 

Back issues only 

Died with issue 4 3 in June 1984 

Index in issue 26 

Colin Morle 

32 Watchyard Lane 

Formby 

Near Liverpool L37 3JU 

England 

Sorcerer Group International 

c/o Don Gottwald 

POB 33 

Madison Heights, MI 48071 

U.S.A. 

Back issues from Gottwald at: 

19967 Rosin Dr. 

Mt. Clemens, Ml 48044 

U.S.A. (about $18 per volume for vols. 

2 to 5) 

now Sorcerer Group International 

(8 times a year) 
Tommy Stokes (or Ed King) 
Route 1. Box 121 
Everton, AR 72633 
U.S.A. 



ISIS (12 a year) 

c/o Maurice Dow 

84 Camberley Crescent 

Brampton, Ontario L6V 3L4 

Canada 

Sorcerer User Group 

of South Australia (12 a year) 

c/o Don Ide 

14 Scott Rd. 

Newton, South Australia 5074 

Australia (index in issue 51) 

Exidy Sorcerer Gebruikers Group 

(6 a year) 
Published in Dutch with full English 

cover-to-cover translation a month 

later 
Index in issue 1 5 

Redactie ESGG 

P/a Postbus 510 
NL-1000 Amsterdam 
The Netherlands 

Sorcerer User Group Schweiz 

Monthly/in German 

CH 3038 Kirchlindach 
Switzerland (index in issue 50) 

Sorcerer Computer Users 
of New Zealand 

Monthly, some Sorcerer material 

c/o Selwyn Arrow 
POB 6210 

Auckland, New Zealand 

I won't give prices since they will change 
and many of the above don't know rates 
to the U.S. since no one has asked before. 

Here are some software sources for the 
Sorcerer that you might want to keep on 
file: 



Roger Hagan 

1146 Fairview Ave. North 
Seattle. WA 98109 

System Software 

1 Kent St. 

Bicton. Western Australia 6157 

Australia 

Nigel Yeo 

24 Bodmin Ave. 
Macclesfield. Cheshire 
England 

Calcom BV 

Nijverheidsstraat 22 
NL-2802 AL Gouda 
The Netherlands 

Softdeal 

Postbus 85 
NL-1135 ZJ Edam 
The Netherlands 



Computer Collect ief 

Amste! 312 (t.o. Carre) 
NL-1017 AP Amsterdam 
The Netherlands 

And some hardware help, firmware, and 
repair services: 

B |. (Bob) Freeman 

414 Olive Way 

Seattle. WA 99202 

or 

POB 12 58 

Seattle, WA 98111-12 58 

U.S.A. 

Ion Weather 

Morristown Municipal Airport 
Morristown. NJ 07960 
U.S.A. 



Sorcerer Computers Users 
of Australia 

(12 a year/Airmail) 

Box 2402 

Melbourne, Victoria 3001 

Australia 

Southern California 
Sorcerer Users Group 

(4 to 6 a year casually) 
c/o Cary E. Stewart 
529 South Beachwood Dr. 
Burbank. CA 91506 

U.S.A. 



Arrington (Ensign) Software 

7337 Northview 
Boise. ID 87304 
U.S.A. 

Howard Arrington 

Suite E, 2312 North Cole Rd. 

Boise ID 87304 

U.S.A. (This is an old address.) 

COMTRO Software Development 

Rec. Bonsel Str. 10 
NL-6433 EP Hoensbroek 
The Netherlands 



Tercentennial Technical 

70 Tercentennial Dr. 
Billerica. MA 01821 

U.S.A. 

South Valley Electronics Inc. 

Suite E. 2110 Walsh Ave. 
Santa Clara. CA 95050 
U.S.A. 

Mentzer Electronics 

590 South Hill Boulevard 
Daly City CA 94014 

U.S.A. 



22 BYTE' APRIL 1985 



LETTERS 



The Brothers Van Montfort 

(Gebroeders van Montfort) 
Smedestraat 13 
NL-6411 CR Heerien 
The Netherlands 



Daniel Say 
Vancouver, BC Canada 



Apple II Blues 



I happened on Mr. Dennis Doms's letter 
("A Call for Better Apple Support," 
September 1984, page 14) and but for 
near-identical circumstances, I would have 
dismissed it as one of those individual 
quirks in product support. I fully endorse 
Mr. Doms's comments. His perceptiveness 
of the ProDOS documentation problem is 
particularly commendable when one con- 
siders the fact that he is experienced in 
DOS 3.3! 

In early March of this year our 
information-processing group decided 
that a small "user-friendly" micro might 
provide quick turnaround for some of our 
project record-keeping applications. 
Although the senior program manager 
was a Kaypro owner, he carefully avoided 
imposing his own preference on the 
organization. An Apple 11+ owner made 
a seemingly sound recommendation that 
we get an Apple lie with duodisk and a 
small dot-matrix printer. 

Two days later, the Apple He arrived with 
its display, an Epson printer, and the 
duodisk. VisiCalc and two PFS packages 
also were provided to get things started. 
A seeming ton of books accompanied the 
units, A quick pilot run with VisiCalc and 
PFS was made, and a short training ses- 
sion was held for floor engineers and proj- 
ect managers. 

People experienced losses of whole 
files, mutilation of data, and I/O errors 
using PFS. The possibility of human error 
was explored, and new data backup pro- 
cedures were instituted. Repair of the 
duodisk decreased the variety of I/O 
errors but did not eliminate them. Sub- 
stitution of the duodisk with two stand- 
alone drives did not help. The Apple 
technician blamed the problem on PFS. 
The salesman who had originally sold us 
the Apple and the software then sold us 
Appleworks. The users read Appleworks 
documentation, more training sessions 
were held, new files were established, data 
was reentered. Within a day there were 
more I/O errors and losses of data 
reported. The Apple dealer then replaced 
the main logic board and again worked on 

{continued) 



More terminals 



without more computer 



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Inquiry 41 APRIL 1985 • B Y T E 23 



LETTERS 



the duodisk. This finally solved the prob- 
lem (both Appleworks and PFS work we!! 
now). 

A task request arrived on my desk to 
write some printer set-up utilities and a 
project accounting package for the Apple. 
Coming from a CP/M-86 TRSDOS and 
1BM-VS background, 1 didn't instantly see 
the relationship between the Apple DOS 
and BASIC. The undocumented "loading 



of Integer BASIC was disturbing. My first 
effort on the printer routines worked well 
enough (after I found that I/O had to be 
directed to physical card slots and that the 
Apple did not support logical devices') 
Since the design for the project account- 
ing task involved multiple files and several 
large arrays. I broke out the books. 

As in Dennis Doms's case, we had 
received a ProDOS users manual and an 



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Apple He owners manual. These had no 
substantive information that documented 
the machine or Apple's software. The 
paper quality was nice; the indexes and 
tables of contents had errors. The ProDOS 
manual talked about differences from DOS 
3.3 and seemed aimed at people familiar 
with Apple DOS. The ton of books also 
included books for the 80-column card. 
the Apricot printer card, a duodisk 
manual, a pamphlet for the display, and 
several excellent manuals for VisiCalc. PFS. 
and the Epson printer. 

I called our dealer and was told that we 
deserved a ProDOS Programmer's Manual 
since it had been out of stock when we 
bought the machine. He did not have one 
but would special-order one for us. I de- 
scribed my needs for documentation and 
was told I would need the Applesoft and 
DOS 3.3 manuals and that these were 
extra-cost items. 1 was told to ignore all 
references to Integer BASIC since it was 
an "archaic tongue" and no documenta- 
tion was in print for it. (Undocumented 
modules of an operating system bother 
me!) The pricing was confused, but a total 
of $70 plus tax finally went on our pur- 
chase order. We soon received a bill. Two 
trips to the dealer and multiple phone 
calls over a six-week period failed to pro- 
duce the manuals. There was talk of them 
being in a warehouse, then being back- 
ordered from Apple, then being out of 
print. Finally, with a Friday promise that 
they would be mailed on Monday. Ac- 
counting paid the bill. Two weeks later the 
dealer produced an explanation that the 
required manuals were unavailable from 
Apple and there was no projected delivery 
date. 

TWo months after the first phone call 
about documentation, our "free" ProDOS 
Programmer's Manual arrived. It was much 
as Mr. Doms describes— dependent on the 
DOS 3.3 and Applesoft documentation. 
The senior program manager visited the 
Apple dealer and with some hostility of- 
fered an invitation to small-claims court. 
The salesman then gave us his personal 
copies of the DOS 3.3 and Applesoft 
manuals. We then considered that the pur- 
chase order had been filled! 

Our company's purchasing agent will en- 
sure that no more business is directed to 
the Apple dealer who sold us the He. 
Apple's viability in the microcomputer 
business is doubted by every engineer, 
project manager, and technician who has 
been associated with our He. We now have 
three more Kaypro owners. At the office 
I'm pleased by the Displaywriter with its 

[continue^ 



24 BYTE* APRII 



198^ 



Inquiry 35 1 



If you don't have a 

Hercules Graphics Card, you could 

end up looking like this: 



"I know, because one day it hap- 
pened to me . . . 

"I was running some routine 
tests on a non-Hercules mono- 
chrome graphics card when I 
was struck by a severe case 
of low resolutionitis. I'm the 
president of Hercules and 
that's me exhibiting the 
symptoms of the disease 
in its advanced stages. Not 
a pretty sight, is it? 

"What causes low res- 
olutionitis? Experts point 
to ordinary monochrome 
graphics cards with 
coarse, hard-to-read 
graphics. A bad case of eyestrain may 
develop if action is not taken immediately. 

"Fortunately for me, a Hercules Graphics 
Card was nearby. A quick change brought 
soothing 720 x 348 graphics. That's twice 
the resolution of ordinary 640 x 200 graph- 
ics cards. 

"Which means better graphics for 
Lotus™ 1-2-3™ Symphony" Framework," 
pfs:Graph," Microsoft* Chart and Word, 
SuperCalc3; AutoCacT," and dozens of 
other programs. 

"Including Microsoft Flight Simulator, 
now Hercules compatible! 

"Oh, and don't forget that a parallel 
printer port is standard on the Hercules 
Graphics Card, not an extra cost option. 

"Now, if you're worried about buying 
a new product that hasn't had all the bugs 




worked out, relax. Hercules has 
sold more monochrome graphics 
cards for the IBM PC,XT™ and AT" 
than anyone else in the world. 

"So . . . you're convinced that 
you should buy a Hercules 
Graphics Card. Now, steer 
clear of cheap imitations. 
You may save a few bucks, 
but you won't get all of 
these five essential features 
which only Hercules has: 

"1) A safety switch that 
helps prevent damage to 
your monitor, 2) the 
ability to keep an IBM 
or Hercules Color Card 
in your system, 3) the ability to use the PC's 
BASIC to do graphics, 4) a Hercules de- 
signed chip that eliminates 30% of the parts 
that can go wrong, and 5) a two year warran- 
ty, because we think reliability is something 
you should deliver and not just talk about." 
Call 1-800-532-0600 Ext 408 for the 
name of the Hercules dealer nearest you 
and we'll rush you our free info kit. 




Hercules. 

We're strong on graphics. 



Address: 2550 Ninth St., Berkeley, CA 94710 Ph: 540-6000 Telex: 754063 Trademark/Owners: Hercules/ Hercules Computer Tech; IBM, XT, AT/ IBM; Lotus 1-2-3, 
Symphony /Lotus Development; Framework/Ashton-Tate; Microsoft /Microsoft; pfs: Graph /Soft ware Publishing; SuperCalc3/Soreim-IUS; AutoCad/AutoDesk. 



Inquiry 183 



APRIL 1985 • BYTE 25 



LETTERS 



p-System. I am quite happy with my 
TRS-80 at home. Recent clamorings by my 
offspring for Macintoshes coincided with 
the lie problems. Both kids and their 
friends understand why I hesitated then 
made another choice for them. 

This is my first experience with an Apple. 
I have no personal need to make it more 
detailed or extended in time. I find the 
documentation to be shallow, the I/O im- 
plementation crude (even when measured 
against 1980 standards), and the service 
haphazard, i more carefully assess what 
Apple owners and users have to say about 
their machines. 

My feelings might not be quite so strong 
if only the hardware or the documentation 
had been screwed up. The infant mortali- 
ty in the hardware combined with docu- 
mentation hassles have heavily under- 
scored the flaky sales support and the 
mediocrity of the operating system and 
language. Color Apple with a worm in it! 

By contrast, Digital Equipment Corpora- 
tion provides us with singularly outstand- 
ing support for our Rainbow. That system 
is supported by an excellent certification 



program for third-party software. If DEC 
says that a particular package such as 
CTOS or Lotus 1-2-3 will run on the Rain- 
bow, you can bet the company has tried 
it and within the range of their tests has 
found no implementation bugs. Our IBM 
Displaywriters use CP/M-86 and UCSD p- 
Systems that have outstanding support 
from D/R and Softtech as well as IBM. My 
TRS-80 came with a language reference 
manual and DOS manual as well as 
owners/operators manuals. The additional 
technical reference manuals were readily 
available from the dealer at nominal 
charges. Every Tandy manual was well 
written, pretty much stand-alone, and had 
a good reference appendix. The indexes 
and table of contents did not contain 
errors in page numbers. 

Just out of curiosity. I priced documen- 
tation at our local Commodore dealer and 
at a nearby Tandy Computer Center. Much 
of it is free with the system, and the prices 
on the remainder are moderate— what's 
more, it's readily available. 

Paul M. Hine 
San Diego, CA 



When a manufacturer sells a computer 
and withholds information on that com- 
puter, the computer's worth is in direct 
proportion to the amount of information 
one receives. No information means the 
computer is worthless, A computer is 
unique in this regard. If you buy a car, 
someone can always drive it or fix it 
without a shop manual. Try programming 
a computer to do something you want it 
to do without information on the I/O ports 
or the memory map. Try getting a com- 
puter fixed that no one has schematics for. 
Of course, somebody can always charge 
you three or four hundred dollars and 
replace the entire main circuit board when 
only a twenty-cent chip may be defective. 
You don't need a schematic to do that. 
After all, the manufacturer makes a lot of 
money selling you a new circuit board for 
$400 when you don't need one. 

I have an Apple He. I was originally in- 
terested in the compact Apple lie because 
of its built-in disk drive and its ability to 
be powered from a 12-volt car battery. 
Apple computer promised some day Real 

(continued) 



YEAR WARRANTY ON CARD AND DRIVE 



10 Mbyte 



SATISFACTION 
GUARANTEED 



Suggested retail price $1095 

SPECIAL 
SALE PRICE 



'945 



100% refundable within 30 days. 

For IBM PC* & compatibles. 2 
Years Warranty on disk drive and 
controller card. 

• Half-height drive with 
controller card 

• Low error rate 

• Low power 

• High performance and 

» reliability 
• Easy installation 

20 Mbyte for ' 1,495. 



TO ORDER SEND CHECK OR 
MONEY ORDER TO: 

Llnd e Technology, Inc. 

8820 S. Sepulveda Blvd., 

Suite 204 

Los Angeles, CA 90045 

OR CALL TOLL FREE: 

I (800) 227-2400 ext. 974 

in California call 

I (800) 772-2666 ext. 974 
Visa and MasterCard accepted. 

California residents add 6/2% sales tax. 



For dealer Inquiry and more 
Information call: {211} 215 94*4 

•IBM is a registered trademark of International 
Business Machines Corp. 



Yes, send me more 
information on: 

□ 10 Mbyte Disk Drive 

□ 20 Mbyte Disk Drive 

Linde Technology, Inc. 

8820 S. Sepufveda Blvd., Suite 204 
Los Angeles, CA 90045 





26 BYTE • APRIL 1985 



Inquiry 235 



A few smart reasons 
to buy our smart modem : 



Features 



Ven-Tel Hayes 

1200 PLUS 



1200 and 300 baud, auto-dial, auto-answer 

Compatible with "AT" command set 

Can be used with CROSSTALK-XVI or Smartcom II software 

Regulated DC power pack for cool, reliable operation 

Eight indicator lights to display modem status 

Speaker to monitor call progress 

Attractive, compact aluminum case 

Two built-in phone connectors 

Compatible with The Source and Dow Jones News Retrieval 

Unattended remote test capability 

Phone cable included 

Availability 

Price 



Yes 


Yes 


Yes 


Yes 


Yes 


Yes 


Yes 


No 


Yes 


Yes 


Yes 


Yes 


Yes 


Yes 


Yes 


No 


Yes 


Yes 


Yes 


No 


Yes 


Yes 


Now 




$499 


$6 



The Ven-Tel 1200 PLUS offers high speed, 
reliable telecommunications for your per- 
sonal computer or terminal. Whether you 
use information services or transfer data 
from computer to computer, the Ven-Tel 1200 
PLUS is the best product around. Available 
at leading computer dealers and distribu- 
tors nationwide. 

Also from Ven-Tel: internal modems for the 
IBM and HP-150 Personal Computers with 
all of the features of the 1200 PLUS. 

You choose. The Ven-Tel 1200 PLUS- 
the smartest choice in modems. 



^nofcnta"*^ 



Ven-Tel Inc. 

2342 Walsh Avenue 
Santa Clara, CA 95051 
(408) 727-5721 



'•***%? 



^Sfe* 1 



Crosstalk is a trademark of Microstuf: Hayes and Smartcom II are trademarks of Hayes Microcomputer Products. 
Inquiry 394 



APRIL 1985 ♦ BYTE 27 



E ■ .• '■'-'■- " I si : 



HP 






NOTE* 







xsm 




Borland's SideKick 
Software Product of theYear 



SideKick is InfoWorld Software Product of the Year. It won over 

Symphony. Over Framework. Over ALL the programs advertised in 

this magazine. Including, of course, all the "fly-by-night" SideKick 

imitations. SideKick .... Simply the best. 



fomestie Sales K&JL1 338. 

ntematioaal Sales SOT 55,88 i 

Iofai Sales 358,88 385.88 45 

C.O.G.S. 35.88 38.58 4 

Soplties 31.58 34.65 4 



Sonestic Salts 388.88 

Itttiutittal bits 58,88 

fetal Salts 358.88 

s \6.t. 35.88 

lties 31.58 

i Salts 283.58 



5?. 12 
J 266.25 382.63 345.16 395.13 
help jrprogya* key with iisplasei mate* *£+&* 




Here's SideKick running over Lotus 1-2-3. In the SideKick 
Notepad you'll notice data that's been imported directly from 
the Lotus screen. In the upper right you 
can see the SideKick Calculator. 



iBsssSS 



All the SideKick windows stacked up over Lotus 1-2-3. From 
bottom to top: SideKick's "Menu Window", ASCII table, 
Notepad, Calculator, Appointment Scheduler/Calendar, 
and Phone Dialer Whether you're running WordStar, Lotus, 
dBase, or any other program, SideKick puts all these desktop 
accessories instantly at your fingertips. 



Side 



kick 



looe 



lnfoW< (rid k' t port Card 1984 by Popular 
Computing. Inc.. a subsidiary o/CW 
Communications Inc. Reprinted from 
tafoWorid, 1060 Marsh Road. 
\h nic Park. CA 94025. 



Jerry Poumelle, BYTE: "If you use a 

PC, get SideKick. You'll soon become 
dependent on it." 

Garry Ray PC Week: "SideKick deserves 

a place in every PC" 

Charles Petzold, PC Magazine: "in a 

simple, beautiful implementation of Word- 
Star's block copy commands, SideKick 
can transport ail or any part of the display 
screen (even an area overlaid by the notepad 
display) to the notepad" 

Dan Robinson, InfoWorld: "SideKick is a 

time-saving, frustration-saving bargain . . 




t 



BORIPOD 



Softwares Newest Direction 

M \3 Scons VaueyDrve 



MTrmnATinmAi Scot!s Va,te y CaMoma 95066 

INTERNATIONAL telex 172373 



Symphony, Lotus & Lotus 1-2-3 are trademarks of Lotus Development Corp. dBase 
& Framework are trademarks of Asfrton-Tate. WordStar is a trademark of Micropro 
Internationa) Corp. SideKick is a trademark of Borland international. 




Inquiry 50 



APRIL 19S5 -BYTE 29 



Inquiry 404 



Planning to deduct your PC? 
The IRS just made it tougher. 

According to the Tax Reform Act of 1984, if you want 
to take a business deduction for your personal computer, you 
now must prove you use it more than half the time for 
business. And that proof must be in the form of a daily log. 

You can waste valuable time each day recording your 
use. Or you can use WorkLog to do the job in seconds. 

Considering how much your time is worth, isn't 
$59.95 a worthy investment? 

To order call (206) 526-0711. Or ask for our brochure 
that describes the power and elegance of this state-of-the-art 
software. WorkLog makes it easy. 

WorkLog 

The essential time-saver. "^ 



For IBM-PC \ -XT, -AT, and compatibles. Requires 128k and any version of PC -DOS. 
WyssWare/5207 Ravenna Ave. N.H. /Seattle. WA 98105 



1Q8S Best Western I 



The right place 
at the right price 




Make reservations at any Best Western. 
see your travel agent, or call 

1-800-528-1234. 

"World's largest chain of independently owned and 
operated hotels, motor inns, and resorts" 



LETTERS 



Soon Now to have a liquid-crystal display 
that would draw very little power and 
operate from a battery. 

The first snag I ran into was when 1 tried 
to find out from the Apple He manuals 
what the pin connections were for the 
nonstandard serial-port connector. No 
luck. Nowhere in the manuals that came 
with the computer could 1 find the con- 
nections for the serial interface. 

The next thing I did was call Apple long 
distance. I was put on hold for five minutes 
listening to some music. Needless to say 
it was not high-fidelity Finally, Patty came 
on the line and told me 1 had to call 
another long-distance number in another 
part of the country. Get this, I am in L.A. 
Well 1 called that number, and an answer- 
ing machine came on the line telling me 
to leave my name and phone number and 
my question and they would get back to 
me within 24 hours. Since 1 am in and out 
of the office all day and no one else at 
my office is knowledgeable enough to ask 
intelligent technical questions about 
RS-2 32C interfaces, that might be a prob- 
lem. If Apple personnel happened to call 
back while I was out of the office, at least 
another 24 hours would go by before 1 
could ask the first question. At this rate 
a year or more would go by before I could 
write this assembly-language program to 
talk to the Apple lie The answering 
machine also advised me to contact my 
nearest dealer. 

We have a lot of Apple dealers here in 
L.A. I contacted three of them. None of 
them knew anything more about it than 
I did. One advised me to go to all of the 
bookstores and get a book on the Apple 
lie. I did just that; in fact, 1 bought three 
books. So far, 1 have spent at least 40 
hours of my valuable time, $40 on books, 
and $50 on long-distance phone calls. I 
now know the pinouts on the connectors, 
but that is all the useful information those 
three books could tell me. Absolutely 
nothing else of any value. No memory 
locations for setting up the RS-232C inter- 
face chip or how to write code to send or 
receive data from the RS-232C interface 
in assembly language or BASIC. Nothing. 

Has Apple management grown so 
greedy that it doesn't want people to buy 
any device to hook up to an Apple lie 
unless they buy it from Apple? Does 
Apple want anyone to write and sell soft- 
ware other than Apple Computer? Is 
Apple management so paranoid that 
someone will copy the He that it is afraid 
to document the ROM? Why does Apple 
have an army of lawyers ready to sue 

(continued) 



30 B YTE • APRIL 1985 



NEW PRODUCT NEWS 
FROM TELETEK 



Systemaster II. Responding to 
market demand for speed and in- 
creased versatility, Teletek is proud 
to announce the availability of the 
next generation in 8-bit technology 
— the new Systemaster II! The 
Systemaster II will offer two CPU 
options, either a Z80B running 
at 6 MHz or a Z80H running at 
8 MHz, 128K of parity checked 
RAM, two RS232 serial ports with 
on-board drivers (no paddle 
boards required), two parallel 
ports, or optional SCSI or IEEE-488 
port. The WD floppy disk control- 
ler will simultaneously handle 
8" and 5W drives. A Zilog Z-80 
DMA controller will provide in- 
stant communications over the bus 
between master 
and slave. Add 
to the DMA 
capability a true 
dedicated inter- 
rupt controller 
for both on- 
board and 
bus functions, 
and the re- 
sult is un- 
precedented 
performance. 
Systemaster II will run under 
CP/M 3.0 or TurboDOS 1.3, and 
fully utilize the bank switching 
features of these operating systems. 



SBC 86/87. As the name indi- 
cates, Teletek's new 16-bit slave 
board has an Intel 8086 CPU with 
an 8087 math co-processor op- 
tion. This new board will provide 
either 1 28K or 51 2K of parity 
checked RAM. Two serial ports 
are provided with individually 
programmable baud rates. One 
Centronics-compatible parallel 
port is provided. When teamed up 
with Systemaster II under TurboDOS 
1.3, this 5MHz or 8MHz multi- 
user, multi-processing, combina- 
tion cannot be beat in speed or 
feature flexibility! 




NEW! SBC 86/87 
SYSTEMASTER tf 

AND Z-150 MB 



k 



TELETEK 



4600 Pell Drive 
Sacramento, CA 95838 
(916)920-4600 
Telex #4991834 
Answer back — Teletek 



nquiry 382 




W$BH;j 



m & 



IN BRAZIL: Danvic S.A 
R. Conselheiro Nebias, 1409 
01203 Sao Paulo, Brazil 
Tel: 221-6033 (P A B X) 
Telex: 1123888 CICP BR 






Teletek Z-150 MB. Teletek is 
the first to offer a RAM expansion 
board designed specifically for the 
Z-150/Z-160 from Zenith. The 
Teletek Z-150 MB is expandable 
from 64K to 384K. Bring your 
Z-150 up to its full potential by 
adding 320K of parity checked 
RAM (or your IBM PC, Columbia, 
Compaq, Corona, Eagle, or Seequa 
to their full potential). The Teletek 
Z-150 MB optionally provides 
a game port for use when your 
portable goes home or a clock/ 
calendar with battery backup! 

Evaluate the Systemaster II, SBC 
86/87 or Teletek Z-1 50 MB for 
30 days under Teletek's Eval- 
uation Program. A 

money-back guarantee 
is provided if not com- 
pletely satisfied! All 
Teletek products carry 
a 3-year warranty. 

(Specifications subject to 

change without 
notice.) 



$ mm 



"■• 



Yes, 'v 

I'm interested % 
in information ^ 

regarding: 
□ Systemaster II 
□ SBC 86/87 □ Z-150 MB 
□ Evaluation Program 
□ Teletek's S-100 Board Line 



Name_ 
Company. 
Address 



LETTERS 



anyone if the company even hints of 
manufacturing a machine that will run 
Apple software 9 Hasn't Appie manage- 
ment learned that the more information 
you supply in the box with the computer 
the less money it takes to support the 
product? Is the well-documented IBM PC 
outselling Apple everything 7 

One would think that Apple had learned 
its lesson with the Apple III. The Apple 



111 came with no real documentation as 
well. We all know what happened to the 
Apple III. From what 1 have seen of the 
Macintosh documentation, the Mac is in 
the same boat. 1 would not use a Mac if 
you gave me one. 

The next problem [ found was that the 
RS-232C data-transmission rate in the 
Apple lie was off frequency by just enough 
to prevent the RS232C from working prop- 



ssss 




Graphics Takes A 
Quantum Leap Forward! 




,i ;:.;;, ; I 






1 1 1 1 1 I I I I I ! 1 I I 



THE INOVION PERSONAL 
GRAPHICS SYSTEM FEATURES: 

• The most advanced color mapping 
capabilities available. 

• 250,000 simultaneously displayable 
colors. 

• A palette of 2.1 million colors. 

• Frame Grabber/ Digitizer to capture 
TV, VCR or Video Camera pictures. 

• Quality three-dimensional texture 
capabilities. 

• Built-in Icon/ Menu software. 

• Completely Mouse/Trackball driven. 
Fonts, Brushes, Microscope, Pat- 
terns, and Rotations. 



1 A complete stand alone system. 

1 A 19" enhanced color monitor. 

1 780K Graphics Memory. 

• 512 x 480 pixel display with 24 bits 
per pixel. 

1 RS232C port allows access to all 
system functions and memory. 

1 NTSC composite video and NTSC 
RGB signal. 

1-year warranty on graphics genera- 
tor and 90-day warranty on 
enhanced monitor. 

i Special introductory 30-day satis- 
faction guarantee. 

' Complete system for $4,495 



^t m 



-H-H-H-H-H-t- 



lki:-'..AfirB 



I LjytbnL Utah 84041 
(8k)1 546-|28fe0i 



l^li 



erly. Apparently Apple divided down the 
microprocessor clock crystal to save the $3 
cost of a data-transmission rate crystal. If 
the lie had a schematic in the owners 
manual, any competent computer techni- 
cian would know about the transmission- 
rate problem before purchasing the com- 
puter. I guess that is one of the reasons 
Apple did not put a schematic in the 
owners manual in the first place. The man 
on the Apple hotline told me to take the 
lie into any Apple computer dealer, who 
would fix it at no cost. None of the three 
dealers I contacted had heard of this repair 
program, nor would they do it at no cost. 

If you buy an Apple other than the lie, 
you need your head examined. 

A Commodore 64, although it costs 
much less than the Apple lie is worth at 
least 100 times as much because you can 
use it. You can get a vast quantity of pro- 
gramming and technical information on 
the Commodore 64 in great detail. Infor- 
mation that is necessary to program and 
interface all the things that people need 
a microcomputer for. 

I now own a $1200 paperweight. 

Paul Lamar 
Redondo Beach, CA 

Where Are Apples 
Manuals When You 
Need Them? 

Last night I tried to order an Apple lit 
Reference Manual at my local dealer. 1 was 
told that the manual costs $50, could be 
ordered only in boxes of five, and if 1 
would order five that they would be glad 
to handle my order. Of course I thought 
that 1 would go elsewhere. 

When I arrived home, some back issues 
of Apple Assembly Line had come in the mail. 
I discovered that Texas Apple dealers had 
the same policy and that it extended to 
ProDOS and He manuals as well. Eventual- 
ly I learned that these manuals could be 
ordered by mail from a dealer in New York 
(212-5I2-4IOO). 

Providing access to the fundamental 
hardware manuals for the machine is the 
most minima] level of dealer support 
possible. Perhaps K-Mart does not provide 
access to manuals for the computers it 
sells, but every self-respecting computer 
dealer must do this. 

The poor availability of these manuals 
must in part stem from the fact that they 
are seen as manuals only a hacker or pro- 
fessional software developer would want 
or need. Apparently Apple believes that 
its customers are not likely to grow in 
[continued on page 436) 



32 



B YTE • APRIL 1985 



Inquiry 198 



FIXES AND UPDATES 



C Changes Quickly 



Our December 1984 article "C-Language 
Development Tools" by G. Michael Vose 
(page 119) brought several new C inter- 
preter vendors out of the woodwork. We 
also learned of a name change for one of 
the article's previewed products. 

The Safe C Compiler from Catalytix Cor- 
poration (55 Wheeler St.. Cambridge MA 
02138) is now called the Safe C Runtime 
Analyzer. The product's functions have not 
changed, only the name, to distinguish it 
from production compilers. 

Catalytix also announced the release of 
its Safe C Standalone Interpreter. The in- 
terpreter is a complete C implementation 
that allows the use of any text editor and 
source-code formatting or cross-referenc- 
ing utilities. Code interactively written and 
debugged within the interpreter can sub- 
sequently be complied into executable 
files, using any compiler that conforms to 
the Kernighan & Ritchie (K&R) C-language 
specification. Currently available for the 
IBM PC and other MS-DOS machines, the 
Safe C Standalone Interpreter sells for 



$400. A Macintosh version is under 
development. 

Age of Reason Company (318 East 6th 
St., New York, NY 10003) has announced 
the availability of RUN/C— a C interpreter 
for MS-DOS computers. Distributed by 
Lifeboat Associates (1651 Third Ave. New 
York. NY 10128). RUN/C costs $150. 

RUN/C features a built-in line editor 
similar to the Microsoft BASIC editor, plus 
the capability to use an outside editor. You 
can even compile your C programs from 
within the RUN/C interpreter. RUN/C fully 
implements the K&R specification for C 
but this interpreter has a limit of 2000-line 
programs. 

Gimpel Software (3207 Hogarth Lane, 
Collegeville. PA 19426) markets a C inter- 
preter called C-terp. also for the IBM PC 
and work-alikes using MS-DOS 2.x. C-terp 
costs $300; a demonstration disk is avail- 
able for $45. C-terp also fully implements 
the Kernighan & Ritchie C-language 
specification, includes an editor, and of- 
fers batch-mode operation. C-terp sup- 



ports small or large memory models. 

Lastly, Computer Innovations (980 
Shrewsbury Ave.. Tinton Falls, NJ 07724), 
purveyors of the C86 C Compiler, offers 
Introducing-C a C interpreter designed to 
help the programming novice learn C as 
her/his first language. 

Introducing-C does not fully implement 
the K&R C specification, but it documents 
the differences in a 10-page appendix. For 
example. Introducing-C does not support 
multidimensional arrays, #defines, struct 
and union data structures, the typedef 
declaration, and several other com- 
ponents of C Future revisions to the in- 
terpreter will provide many of the features 
currently missing. Introducing-C's inter- 
preter is upward-compatible with the C86 
compiler. 

Computer Innovations claims that Intro- 
ducing^ is suitable for learning structured 
programming and most of C and for de- 
veloping "medium-sized, non-scientific 
programs." Available for the IBM PC Intro- 
ducing-C costs $95. 



Printer Buffer Messaged 



In the lune 1984 BYTE there were several 
errors in the article "Build a Printer Buf- 
fer" by |ohn Bono (page 142). Richard 
Carl sen from Upton, New York, built the 
printer buffer, encountered and overcame 
some difficulties, and wrote us about his 
travails. Here are some excerpts from his 
letter: 

1 noticed corrections in the November 
1984 BYTE on the ROM listings (page 34). 
but I haven't seen any hardware updates, 
so here are some suggestions for improv- 
ing John Bono's project. 

In listing 1 on page 453 (June BYTE), line 
13 should show EQU 0FFFFH (zero, not 
"oh") and line 17 should be A. 0FFH. 

In the schematic on page 4 50. IC 14 is 
incorrectly labeled 74LSO0 at the top of 
the page IC 14 is a 74LS367A. (I should 
also note that I tried both the 74LS367s 
and 74LS367AS, and they both work fine.) 



Input pins 4 and 10 of IC 14 should be tied 
high or at least not left floating as those 
sections are unused. Floating leads are not 
good practice and could cause some oc- 
casional errors. 

On the middle left on page 450 the data 
lines are in inverse order. DO should be 
D7, D6 should be Dl, and so on until D7 
is DO. They are labeled correctly at the 
Z80 and 2716. 

A useful item to add is a reset switch 
across the 68-/xF (microfarad) cap on pin 
26 of the Z80. I added a 47-ohm resistor 
in series with the switch so discharge of 
the 68-/xF cap is a little more gentle. 

At the lower right on page 452 you'll 
find IC 13 and IC 24 (printer acknowledge 
FF). A signal is missing (G6) at IC 13, pin 
9. Remove pin 4 of IC 24 from + 5 V. Leave 
IC 24. pin 2 connected to + 5 V. Now con- 
nect pin 4 of IC 24 to pin 9 of IC 13. This 



will allow D306 at line 26 on page 4i>3 to 
reset the printer's acknowledge flip-flop. 

On page 452. data lines, strobe, busy, 
and acknowledge to the left of IC 9 should 
be labeled "TO COMPUTER." At the right 
of IC 15 they should be labeled "TO 
PRINTER." 

Be aware that all 4164 RAM chips are 
not created equal. They come in different 
speeds usually designated by a -2 or -3 
suffix. ! have had no trouble with either. 
However, some companies require 128 
refresh cycles over a 2 -microsecond 
period. Others may require 2 56 refresh 
cycles over a 4-microsecond peri< 1. 1 used 
NEC 4164-2 chips and Moste. 4564-2 
chips successfully, both of which require 
128 cycles. Others requiring 2 56 refresh 
cycles gave me occasional errors. 

Another pointer: Watch the power wir- 

{continued) 



APRIL 1985 'BYTE 33 



Inquiry 2 70 



MidWcst 
Micro-Peripherals 



Save with 






Let us earn your trust as we 

have that of others, such as: 

Goodyear • General Motors • US Navy • etc 
Ask for: Sue. Marianne. Kathy, Tim, Rick or Roger 



List Our Price 

PRINTERS 

Star Gemini 1 0X (120 CPS) $399 $219 

Star Gemini SG-10 (NEW!) 299 229 

Star Gemini 15X 549 349 

Star Gemini SG-15 (NEW!) 499 379 

Star Delta 10 f Delta 15 (160 CPS) $CALL$ 

Star Radix 10 / Radix 15 (200 CPS) $CALL$ 

Epson RX 80 (100 CPS) 399 229 

Epson RX-80 F/T + Series (NEW!) 499 289 

Epson FX-&0 + Series (NEW 1 ) 689 389 

Epson FX-100 + Seres (NEW!) 995 599 

Epson JX 80 Color 799 SCALLS 

Epson LQ 1500 (200 CPS) 1495 $CALL$ 

Okidata 92 P (80 Col... 160 CPS) 599 379 

Okidata Apple imagewnter Compatible 699 449 

Okidata 93P (136 Col.. 160 CPS) 999 599 

Okidata Pacemark 24 1 0P (1 50 CPS) 2495 SCALLS 

Panasonic 1091 (120 CPS) 499 299 

Panasonic 1 090, 1 092, 1 093 $CALL$ 

Toshiba 1340P (54 CPS) 985 769 

Toshiba 1351 P (100 CPS) 1855 1299 

DAISYWHEEL PRINTERS 

Brother HR-15XL (17 CPS) 599 359 

Brother HR-25 (23 CPS) 895 619 

Brother HR-35 (32 CPS) 1245 839 

Silver Reed EXP 400 399 279 

Stiver Reed EXP 500 (16 CPS) 599 359 

Silver Reed EXP 550 (19 CPS) 699 439 

Silver Reed EXP 770 (36 CPS) 1295 829 

Star PowerType (18 CPS, Bi-Dir) 499 328 

Juki 6100 (18 CPS, Bi-Dir) 599 399 

Juki 6300 999 749 

Daisywriter 2000 (40 CPS) 1495 899 

IBM PC SYSTEMS 

PC's and PCXT's 

Complete Systems 
Call and Save! 

EXPANSION CARDS 

AST Six Pac Plus 64K, S/P/C+S/W 
QUA DRAM Complete Line 
MEMORY CHIP kit-64K 150ns-9 chips 




269 

$CALL$ 
49 



149 
299 

159 

1395 SCALLS 
1895 SCALLS 
SCALLS 

SCALLS 



289 219 

399 269 

399 239 

699 469 

599 399 



DISK DRIVES 

Teac Half Heights 299 

Teac 2 Drive Kit - Complete 499 

Tandon 100-2 (IBM Standard) 399 

Maynard - 10 Meg. Internal Drive 
Maynard 20MB Tape Backup 
Tali grass Drives w/Tape Backup 
Turbo 10 10 MB Internal Hard Drive 

MODEMS 
Hayes Smartmodem 300 
Hayes Apple 2c Modem Pkg w/Software 
Hayes Apple 2E Modem Pkg w/Software 
Hayes Smartmodem 1200 
Hayes Smartmodem 1 200B w/IBM Software 

MONITORS 

Amdek 300, 310; Color 500, 600, 700 SCALLS 

Princeton Graphics 4x12 Maxi 2 SCALLS 

SOFTWARE 

Lotus 1-2-3, Symphony & Hundreds More SCALLS 

SANYO SYSTEMS 
Complete Sanyo i«i ■ nu/ 
Systems MM L jjg 

Lots of — $899 

Free Software 






OUR PRICE COMMITMENT 

MidWest will try in good faith to beat 
any nationally advertised price. 



Prices subject to change and type errors 



FREE CAROUSE 



Call Today! 

Information - Ordering 

1-f 00-423-82 15 

In C-iio 1-800-321-7731 

C USTOMER SERVICE (513) 663-499 2 

CASH PRICES: Cert, Check, Money Orders, VISA or MC 
C00S {Add $5) AMEX (Add 4%) P.O.s (Add 5%) 

MidW«(t Micro Peripheral! 

(Division of Infotel Jnc j 

135 South Sprtngfteld St 

St Pans. Ohio 43072 



FIXES & UPDATES 



ing to these RAM chips. Pin 16 is ground 
and pin 8 is + 5 V. This is not as you would 
usually expect with 16-pin chips, and I sure 
got caught wiring these wrong. 

On my unit I used a crystal oscillator at 
1 MHz hooked to pin 6 of the Z80. If you 
do this, a IK pull-up resistor or so at pin 
6 will ensure that the "1" levels are 4,0 to 
4.5 V as the Z80 requires there. 

Not all printers and computers handle 
Centronics interfacing in the same man- 
ner. My Kaypro 2, for example, does not 
use the ACK signal. The buffer works fine 
with my Okidata 92 with the Kaypro using 
just the busy signal. Your computer may 
also use other signals such as the "Paper 
Out" line, Consult your printer and com- 
puter manuals or dealer about your 
printer and computer parallel ports before 
starting this project. In most cases you 
should be able to work things out with the 
available signals supplied by the buffer. 

Some new ideas have been suggested 
by other readers of this article for improv- 
ing the project and I'll pass them on. 

1. Multiple dumps by the use of a repeat 

printout switch would be useful. This 



would allow extra copies of a document 
to be printed from the buffer's memory 
without disturbing the computer. 
Recoding of the RAM and some minor 
hardware additions would be necessary, 

2. Self-check of memory. This would also 
require some additional ROM coding. 

3, A printer code preloader, which would 
let you change printer functions (such as 
compressed print mode, character pitch, 
or near letter quality) by sending the 
printer prewritten codes stored in the 
printer-buffer ROM. These could be 
selected by thumb-wheel switch and 
entered to the printer by a push-button 
switch using the remaining port 7 select 
at G7 pin 7 of IC 1 3 as a means of address- 
ing this feature. 

If anybody has completed these or other 
features, please write in to BYTE and let 
the rest of us in on it. This is a great proj- 
ect when it's working. 1 would like to thank 
John Bono for writing this article and for 
his patience with my questions. I wish also 
to thank other readers for their time on 
the phone and exchange of ideas, and 
BYTE for acting as the intermediary. 



Communication on Modem Gets Garbled 



In the What's New section of the Guide to 
the Apple Personal Computers, a special sup- 
plement to the December 1984 BYTE, we 
inadvertently published the wrong picture 
and supplied some incorrect information. 

The picture on page A 136 does not 
depict Multi-Tech Systems' internal modem 
card for the Apple II, but rather it shows 
Multi-Tech Systems' MultiModem 1200/ 
300-bps external modem. 

The single-board MultiModem Me, 
shown here, fits entirely inside Apple II 
series computers and does not require a 
serial card. It operates at 110/300 bps, 
features auto-answer and auto-dial, and 
comes with communications software. The 
list price is $229, which includes free-time 
and subscription discounts to a number 
of database networks, such as Dow Jones 
News/Retrieval Service and the Instant 

Corrections from Commodore 




Yellow Page Service. 

The MultiModem 1200/300 stores up to 
six 31 -digit telephone numbers, detects 
dial and busy tones, and can continuous- 
ly redial busy numbers. It lists for $549. 

Both modems come with two-year war- 
ranties. Multi-Tech Systems Inc. is head- 
quartered at 82 Second Ave. SE, New 
Brighton, MN 55112, (612) 631-3550. 



The model number of Commodore's new 
1 28K-byte computer was incorrectly stated 
in the February What's New section (page 
40). 

The computer is known as the Commo- 
dore CI28 Also, it uses the 8502 micro- 
processor to run Commodore software 



and its Z80 coprocessor runs at 4 MHz. 
The article also described a new high- 
speed disk drive that works with both the 
CI 28 and the C64. In its C64 mode, the 
drive transfers data at 300 cps. While in 
its C128 or CP/M modes, the data rate is 
5200 cps. ■ 



34 B YTE • APRIL 1985 



by ^FTEK 



THE HIGH PERFORMANCE 
NDOM ACCESS TAPE RACK-UP ! 

THE NEXT GENERATION OF TAPE DRIVES. 



DATASAFE STAND ALONE UNIT 

C/W cable (chains off DB-37 connector on rear of computer) 
Has its own booster power supply 
Is easy to install 



DATASAFE INTERNALLY MOUNTED UNIT 

■ Is daisy chained off the existing floppy controller 

■ Requires IBM plug compatible bus and internally selected 
4 channel select floppy disk controller 

■ No additional slots needed 





For IBM XT's and compatibles ■ Incorporates main frame micro reel technology 
I Random access ■ Use of PC DOS and MS DOS commands (tree, path, etc.) ■ MTBF - 20,000 hrs. 

■ Reliable (150,000 load and unload failsafe tested by an independent laboratory) 
C/W software device drivers ■ C/W cable ■ Extremely fast back-ups ■ 10 meg available only 
"1 Priced less than 50% less than the nearest rival ■ ONE YEAR WARRANTY 



The DATASAFE uses industry 
standard V/' tape on a self threading 
2.2 "spool 




1050 Clinton St. 

Buffalo, New York 

14206 

Tel.; (716) 694-5366 Telex: 916428 



<&FTEK 



762 Gordon Baker Rd. 

Willowdale, Ontario 

Canada M2H3B4 

Tel.: (416) 497-0531 or toll free 

1-800-268-5412 Telex: 06-986133 



Business Machines Inc. 

PRIME DEALER DISTRIBUTOR TERRITORIES AVAILABLE. OEM CALLS INVITED. 



You have wanted to do something, 
but the door has been closed . . . 



6 File Edit Icons Uttphuj Search f <mi S1 tji 
HEPUH1 



[wT] 

[wT| 

j gEI 



$12,779.22 

$10,253 89 

$20,145.50 

$6,778.05 



$15,175 90 
$13,020.19 
$22,998.00 
$43,332.00 



$9,765 88 
$13,786.33 
$14,995.43 
$25,790.00 




amount |date ]accl. |neuj 

$6,554 10/28/ 432 Yes 

$233 00 10/28/ 879 Yes 

($9 00) 10/25/ 456 Y*s 

$7,654 3 10/23/ 543 No 

$6.7780 10/19/ 66 No 

C$43 33) 10/19/ 983 No 

$5,656 5 10/17/ 543 No 

$10000 10/17/ 666 Vm 

$1,987 10/12/ 110 No 

$8,887 9 10/10/ 65 Yes 

*7ft <»n in/in/ 777 m» 



Helix is a data-based system, so that once you enter information 
you can use it for anything - reports, lists, analyses, mail merge 
printouts, or even relational look-ups to other data-bases within 
Helix. 



Requires an external drive or hard disk 

512K Macintosh Lisa with MacWorks 
■Supports Hard disks Keypad 15" Imagewriter 

rulud' Helix Program disk Helix Guided Tour disk Helix 
Resource/Work disk User Manual 18-ring project binder 

Reference pad for custom documentation Registration card 
for support & updates 

( Offers Modeless input, interactive query, editing, & report gen- 
eration Text-formatting Calculations between fields & across 
records Object-oriented, icon-based design Relational Look- 
ups List management Mail merge Clipboard & ASCII file 
transfer Special Template tools for form design User defined, 
automatically updated Indexes Unrestricted length & number 
of fields Complete printing options Vertical and horizontal 
autoscroll Visual building blocks for arithmetic, date, text & 
Boolean operators, functions, & values. 




The full functionality of Helix lies within its six 
basic icons. You can "learn by doing" with Helix, 
since it does not get in your way with imposed 
structure or restrictions. You don't have to 
worry about parameters, command codes, or 
"modes". 



turd worW Our mat 

thti ptri«Kl joVitton* 

e*pit*l eommttmwHi 
*nd offw d*v»topwig 
*r»« (<)*o<)r»ph>nc 




All open windows are updated automatically. 
Used here to simultaneously enter project 
notes, see synopses, get phone numbers, and 
display important "global" statistics. 



SOFTCON 

Georgia World Congress Center 

Atlanta, Georgia 

Sunday-Wednesday 

March 31 to April 3. 1985 

10 am to 5 pm daily 

Booth I427 



© 1985 Odesta Corp. 

Odesta Helix is a trademark of Odesta Corporat iun 
Apple, Lisa, and Macintosh are trademarks of 
Apple Computer, Inc. 



Odesta Helix opens the door. 



6 File Edit Ico ns BKgjatj Vp»rt:rt I art! SUflc 
shipping 



* FiIp Edit Icons tli»i>mij Search i mil si^ie 




Format I Vf/! ( r^ "l r- n r~ n t ? — 1^) 

TZT^^fe |To^ip] | pa [Ho?l| CB [S] PS |[[nj|^[ J 



price item ■ item ■ invento 



Now, you don't have to learn a programming language or worry 
ahout "relational algebra". Except for the three numbers you 
see, no typing was used to create these calculations: "If invoice 
amount is equal to or greater than $2500, then don't charge for 
shipping, otherwise charge 2.5$ of the invoice amount" . . . 
"Look up the price for the item in the inventory data-base" . . . 
"Multiply the items price by how many were shipped" . . . 



* File Edit Icons msphsij Search Font style 
Relation 




Helix combines powerful functions with a design that gives you 
direct control. 



Y.i1«.rdg*i SMI Sph*r», Ink 
1225 Narttwjft Pl*cr 
Suit* 33 
Hobok.n N*v J*rs*9 02334 



Thank you (or responding to our questionnaire. 

Hs a fiber-dye specialist working with natural color techniques, 

your peripectiue on the needs and Interests of the members of 

BeMused is particularly welcome. 

The results of our suruey are uery Interesting. 

55% of current members ttaue never attended a regional workshoi 

or seminar. 

39% said that they would be interested in a co-op buying seruice 

pay as much as 530/year to help defray administrative enpenses. 

There were 9 graves ef at least IS people laterested la 

participating ia lae newly proposed special interest clat 

ll>« «■«•■• fittmr-rrmtt nmmmrmtmii l«raa* nt tKa«» Mi* 



Built-in text formatting lets you combine infor- 
mation in a new way for mail merge letters, 
memo's, reports or free-form comments. 



Helix provides a unique place to work because 
it takes a different approach. 

It is based on the idea that we discover 
the important questions, relationships, and 
connections between things by working with 



(So we need to be able to work with words and 
numbers in many different forms). 

That our own experience, perception, and 
understanding are the basis of true "knowledge 
work". 

And that this process can be both productive 
and playful, intently serious and intensely 
enjoyable. 

(So we need a technology that is flexible, 
accommodating, and directly responsive to our 
actions and style of dialogue). 



Gocs/a X. 


H= 


L 


► 


w 






Kmm 



Odesta, MHO On 
(800) 323-5423 



Drive. Northbrook, II 60062 ( ISA ) 
ioiy « 312} i98 5615 



A Data-Based Information Management & 
Decision Support System 



ANOTHER KlN6-6tZB 
ACVANTA&E ClToH 
HAS OVER OTHER 
PRINTERS/ 

The biggest name in printers might be a 
name you don't even know. C. Itoh. 

But people who do know C. Itoh printers 
know that they've always had a big edge in 
speed. And an edge in reliability. 

And an edge in support, with service centers 
nationwide and the backing of a worldwide 
$60 billion parent company. 

And now, C. Itoh ProWriter™ dot matrix and 
StarWriter™ daisy wheel printers have a big 
edge in price, too. 

We've been able to reduce our retail prices 
an average of 30%, because we've reduced 
our distribution costs by selling directly to our 
dealers. 

It's given us a price advantage of $80 to 
$1,000 over what the competition has to offer. 

Take a look. 




DOT 
MATRIX 


BRAND MODEL NO. 


SPEED 

LINES PER 
MINUTE 


PRICE 

MFG SUGG 
RETAIL 


C. ITOH 


7500 


54 


$ 289 




EPSON 


RX-80FT 


44 


269 


STAR 


GEMINI 10X 


48 


399 


IBM 


5152 


36 


494 










DAISY 
WHEEL 




CHARACTERS 
PER SECOND 




C ITOH 


A10-20S 


29 


$ 669 


QUME 


LP20 


20 


799 


NEC 


2010 


20 


950 


DIABLO 


620 


20 


995 










C. ITOH 


F10-55 


58 


1,449 


DATA 
PRODUCTS 


DP55 


55 


1,895 


QUME 


1155 


55 


1.995 


NEC 


7700 


55 


2,495 



C. Itoh. The best selling printers in the world, 
with 1.7 million printers sold in 1984 alone, now 
have the best prices, too. 

For more information call toll-free 
1-800-423-0300. Or write C. Itoh Digital 
Products, Inc. 19750 South Vermont Avenue, 
Suite 220, Torrance, CA 90502. 



CoLTLffiLrO 



1984 News Group Chicago. Inc. 



twees 



OUR 
PftCBS 




38 BYTE • APRIL 1985 



'" ProWriter & StarWriter are Trademarks of C. Itoh Digital Products, Inc 
€ 1985 C Itoh Digital Products, Inc. 

Inquiry 5 5 for Dealers. Inquiry 56 for End Users. 



WHAT'S NEW 



Thermal Printer Has Full Graphics Ability 



General Electric recently 
announced the Model 
3-8100, a $300 thermal- 
transfer letter-quality printer 
with full graphics capability. 
Although the printer comes 
standard with a Centronics- 
type parallel connector, GE 
will also sell two compatibili- 
ty modules for $89.95. One 
allows direct connection to 
the Atari 400/800 com- 
puters and Commodore's 64 
and V1C-20; the other 
module permits direct con- 
nection to the IBM PCjr. 

The Mode! 3-8100 prints 
at two speeds: 50 cps in 
draft mode and 2 5 cps in 
letter-quality mode. At both 
speeds, the printer is quiet. 
A 16-dot print head pro- 
vides high-resolution dot- 
matrix output. 

The Model 3-8100 can use 
single-sheet, roll, or 9!^-inch- 
wide fanfold paper. It prints 




The General Electric 3-8100 dot-matrix printer, 



on thermal paper if you 
remove the cartridge. Each 
ribbon cartridge costs about 
$6 and provides about 
100.000 characters. 

The manufacturers sug- 
gested retail price for the 



Model 3-8100 is $299.95. 
Contact General Electric Co.. 
Consumer Electronics Busi- 
ness Operation, POB 4840. 
Electronics Park, Syracuse, 
NY 13221, (315) 456-3304. 
Inquiry 600. 



Keyboard Enhancement Has Macros, Data Encryption 



Borland International's 
SuperKey is a RAM- 
resident keyboard-enhance- 
ment program featuring 
macros and automatic data 
encryption. This program 
lets you define, edit, save, 
load, and recall macros on 
your IBM PC in real time. 

SuperKey has a memory- 
resident full-screen macro 
editor that can be pulled 
down on top of a currently 
running program. The pro- 
gram supports single-key 
macros, user-definable 
macro titles, help menus, 
date/time information, alter- 
nate arrow-key definition, 
key-click switching, keyboard 
lock/unlock, sound effects, 
and color control. 



With SuperKey, you can 
recall from a command 
stack the last 20 commands 
entered. These are displayed 
in a menu window that lets 
you select, edit, and reuse 
the commands at the DOS 
command level or in a pro- 
gram. SuperKey has a cut- 
and-paste capability that 
permits any data to be 
copied from the screen, 
stored within SuperKey 
under any key, and then 
moved into another 
application. 

The SuperKey data- 
encryption function lets you 
encode files in two modes. 
In the first mode, no second 
file is created, thus saving 
disk space. In the second 



mode, you can encrypt 
binary files by transforming 
them into ASCII. This lets 
you transmit these files over 
telephone lines. The recip- 
ient of the files decrypts 
them using a special "key." 
Also featured is a display 
burn-in protection capability 
that automatically switches 
off a monitor's video signal 
when no activity is detected 
for a reasonable length of 
time. The display is automat- 
ically reactivated when any 
key is pressed. The program 
is priced at $69.95. Contact 
Borland International, 4113 
Scotts Valley Dr., Scotts 
Valley, CA 95066. (408) 
438-8400. 
Inquiry 601. 



GE TVs Also 
Serve As Monitors; 
Modem Unveiled 

Two new television sets 
from General Electric 
can also serve as your com- 
puter monitor. The Model 
13BC5509 is a 13-inch color 
monitor, and the Model 
12XR5204 is a 12-inch 
black-and-white monitor. 

Both units handle 80-char- 
acter-per-line displays and 
feature a display width- 
reduction capability that 
prevents character loss at 
the screen's edge. They ac- 
cept composite-video input 
as well as standard antenna 
connectors and are compati- 
ble with most home com- 
puters from Apple, Atari. 
Commodore, IBM, and other 
manufacturers. 

Suggested retail price is 
$489.95 for the color moni- 
tor and $129.95 for the 
black-and-white unit. 

In a concurrent announce- 
ment, GE introduced the 
Model 3-8200 direct/acoustic 
modem. This 300-bps mo- 
dem has a standard 
RS-232C cable, and optional 
cables are available for 
direct connection to Atari or 
Commodore computers. 

The 3-8200 has automati- 
cally switchable answer/ 
originate modes and once 
tied into a database, it auto- 
matically adjusts for full- and 
half-duplex operation. 

The Model 3-8200 modem 
has a suggested retail price 
of $119.95. Contact General 
Electric Co., Consumer Elec- 
tronics Business Operation, 
POB 4840, Electronics Park. 
Syracuse. NY 13221, (315) 
456-3304. 
Inquiry 602. 

{continued) 



APRIL 1985 -BYTE 39 



WHAT'S NEW 



Kaypros 286i Is an IBM PC AT Compatible 



Kaypro's 286i, scheduled 
for formal introduction 
last month, is compatible 
with IBM's Personal Com- 
puter AT. It features a 
6-MHz 80286 processor, two 
parallel ports, one serial 
port, and two l.2-megabyte 
5!4-inch floppy-disk drives. 
The system's main board 
comes with 5 1 2 K bytes of 



RAM, expandable to 640K 
bytes; expansion cards can 
supply an additional 15 
megabytes of RAM to the 
system. 

Three of the system's eight 
IBM-compatible expansion 
slots are occupied, leaving 
five for additional peripher- 
als or memory. The 286i's 
84 -key keyboard is also 



functionally compatible with 
the PC AT's. 

Standard with the system 
are color graphics (RGB and 
composite, both of which 
are compatible with the IBM 
graphics-display card) and a 
clock/calendar with battery 
backup. Software bundled 
with the system includes 
Micropro's WordStar, Mail- 



Merge, InfoStar, CalcStar, 
tutorials, and Microsoft's 
GW-BASIC interpreter. 

The Kaypro 286i has a 
suggested list price of 
$4 5 50. For more informa- 
tion, contact Kaypro Corp., 
533 Stevens Ave., Solano 
Beach, CA 92075. (619) 
481-4300. 
Inquiry 603. 



130-cps Printer Is Compatible with Epson RX-80 



The Aero from Alphacom 
is a 130-cps dot-matrix 
printer that's compatible 
with existing software and 
graphics supporting Epson's 
RX-80 series printing pro- 
tocols. Alphacom has op- 
timized the Aero's print 
speed with the inclusion of 
path-seeking logic and a 2K- 



byte buffer. 

Aero produces the stan- 
dard 96-member ASCII 
character set, and it lets you 
define up to 96 characters 
for custom applications. It 
forms 6- by 8-dot characters 
with true descenders in a 6- 
by 9-dot matrix grid using a 
9-wire print head. The print 




Alphacom s Aero is compatible with Epson's RX-80. 



ALL Card Allows 4 Megabytes RAM in IBM PC 



head outputs either 480 or 
960 dots per line in either 
alphanumeric or bit-image 
modes. 

Manuscripts printed out 
on the Aero can display any 
mixture of superscripts, 
subscripts, double-strike, 
enlarged and emphasized 
type, underlining, text, and 
graphics on the same line. 
Aero will print out an 
original and three copies 
using perforated or regular- 
bond paper. 

Indicators for power-on, 
on-line, paper-out, and ready 
are located on the top right 
side of the Aero along with 
its operator controls. Aero 
comes with a self-test fea- 
ture, and it uses standard 
Epson ink cartridges. 

RS-232C and Centronics- 
type parallel versions of 
Aero are available. The sug- 
gested retail is $249.95. 
Contact Alphacom Inc., 2323 
South Bascom Ave, Camp- 
bell. CA 95008, (408) 
559-8000. 
Inquiry 604. 



ALL Computers' ALL 
Card ATI features a 
custom CMOS memory- 
management unit (MMU) 
processor, in addition to 
other memory and interface 
enhancements, on a single 
IBM PC expansion card. The 
ATI comes with a clock/ 



calendar, a serial port, the 
MMU, and room for 1 
megabyte of on-board 
memory using 2 56K-byte 
chips. You can add up to a 
total of 4 megabytes to the 
system. 

With 2 56K bytes of 
memory, the ATI ALL Card 



is $1295. Without the MMU. 
it's $795. A version with 
neither memory nor the 
MMU is $395. Contact ALL 
Computers Inc., Suite 501, 
110 Bloor St. W. Toronto, 
Ontario M5S 2W7, Canada. 
(416) 960-0111. 
Inquiry 605. 



Internal Hard Disk 
for PC AT 

Control Data Corporation 
is now shipping a 30- 
megabyte hard-disk drive 
that fits inside IBM's PC AT 
Called the StorageMaster 
630, this drive has a typical 
access time of 30 milli- 
seconds, which is reported 
to be approximately 2 5 per- 
cent faster than the native 
IBM drive. 

The StorageMaster 630 
uses the PC AT's resident 
disk controller and is ship- 
ped with adaptive software 
that lets you tweak it for 
operation with PC-DOS 3.0. 
The software gives you the 
ability to logically partition 
and format the disk, and in- 
cludes diagnostic routines. 

A pair of StorageMaster 
630s can be tucked side-by- 
side within the PC AT's 
cabinet. Installing the 
StorageMaster 630 into the 
PC AT housing is said to re- 
quire less than one hour. 

Disk image or selected 
file-backup capabilities for 
the StorageMaster 630 are 
available through use of 
Control Data's 45-megabyte 
StorageMaster 74 5 !4-inch 
cartridge streaming-tape 
backup system. 

The suggested list price 
for the StorageMaster 630 is 
$2145. Contact Control Data 
Corp., 8100 34th Ave. S, 
POB 0, Minneapolis, MN 
5 5440, (800) 328-3390. 
Inquiry 613. 

[continued] 



40 B YTE ■ APRIL 1985 




They said it couldn't be 
Borland Did It.Turbo Pascal 3j0 



The industry standard 

With more than 250,000 users worldwide Turbo 
Pascal is the industry's de facto standard. Turbo 
Pascal is praised by more engineers, hobbyists, 
students and. professional programmers than any 
other development environment in the history of 
microcomputing. And yet, Turbo Pascal is 
simple and fun to use! 



TURBO TURBO MS 
3.0 2.0 PASCAL 



COMPILATION SPEED 



EXECUTION SPEED 



CODE SIZE 



BUILT-IN INTERACTIVE EDITOR 



ONE STEP COMPILE 

(NO LINKING NECESSARY) 



COMPILER SIZE 



TURTLE GRAPHICS 



BCD OPTION 



PRICE 




Portability 

Turbo Pascal is available today for most computers 
running PC DOS, MS DOS, CP/M 80 or CP/M 86. A 
XENIX version of Turbo Pascal will soon be announced, 
and before the end of the year, Turbo Pascal will be 
running on most 68000 based microcomputers. 

An Offer You Can't Refuse 

Until June 1st, 1985, you can get Turbo Pascal 3.0 for 
only $69.95. Turbo Pascal 3.0, equipped with either the 
BCD or 8087 options is available for an additional 
$39.95 or Turbo Pascal 3.0 with both options for only 
$124.95, As a matter of fact, if you own a 16 Bit 
computer and are serious about programming, you 
might as well get both options right away and save 
almost $25. 

Update policy 

As always, our first commitment is to our customers. 
You built Borland and we will always honor your 
support. 

So, to make your upgrade to the exciting new version of 
Turbo Pascal 3.0 easy, we will accept your original Turbo 
Pascal disk (in a bend-proof container) for a trade-in 
credit of $39.95 and your Turbo87 original disk for 
$59.95. This trade-in credit may oniy be applied toward 
the purchase of Turbo Pascal 3.0 and its additional BCD 
and 8087 options (trade-in offer is only valid directly 
through Borland and until June 1st, 1985). 



O Benchmark run on an IBM PC using MS Pascal version 3.2 and 
the DOS linker version 2.6. The 179 line program used is the "Gauss 
Seidel" program out of Alan R. Miller's book: Pascal programs for 
scientists and engineers (Sybex, page 128) with a 3 dimensional 
non-singular matrix and a relaxation coefficient of 1.0. 



The best just got better: 
Introducing Turbo Pascal 10 

We just added a whole range of exciting new 
features to Turbo Pascal: 

• First, the world's fastest Pascal compiler just got 
faster. Turbo Pascal 3.0 compiles twice as fast as 
Turbo Pascal 2.0! No kidding. 

• Then, we totally rewrote the file I/O system, and 
we also now support I/O redirection. 

• For the IBM PC versions, we've even added 
"turtle graphics" and full tree directory support. 

• For all 16 Bit versions, we now offer two addi- 
tional options: 8087 math coprocessor support 
for intensive calculations and Binary Coded 
Decimals (BCD) for business applications. 

• And much much more. 

The Critics' Choice. 

Jeff Duntemann, PC Magazine: "Language 
deal of the century . . . Turbo Pascal: ft 
introduces a new programming environment and 
runs like magic" 

Dave Garland, Popular Computing: "Most 
Pascal compilers barely fit on a disk, but Turbo 
Pascal packs an editor, compiler, linker, and run- 
time library into just 29K bytes of random- 
access memory." 

Jerry Poumelle, BYTE: "What I think the 
computer industry is headed for: well 
documented, standard, plenty of good features, 
and a reasonable price," 




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Software's Newest Direction 

4113 Scotts Valley Drive 
ikiTrnkiATinMAi $ cotts Valle ¥ California 95066 

INTERNATIONAL telex. 172373 

Inquiry 47 
Turbo Pascal is a registered trademark of Borland International, inc. 




WHAT'S NEW 



S-100 Graphics Cards Produce TV-Quality Images 



T he S-Series of color- 
graphics products lets 
you produce images to the 
maximum resolution of 
NTSC and PAL television 
standards on Cromemco's 
68000- based S-100 com- 
puter systems. The S-Series 
comprises the previously an- 
nounced SDD Color Digitizer 
Interface, plus four new 
S-100 (IEEE-696 standard) 
bus cards. 

The SVID Color Video 
Generator Board works with 
the SDMA Video Memory 
Controller card to generate 
color images by panning 
over a virtual 1024- by 
1024-pixel image The NTSC 
version displays 756 by 484 
pixels, while the PAL card 
set generates a 756- by 
577-pixel image. Depending 
on graphics memory, up to 
8 bits of data can be allo- 
cated per pixel to select up 
to 2 56 colors from a palette 
of 2 56,000. 

The 2 56KTP card comes 




S-Series color-graphics cards from Cromemco. 



with 2 56K bytes of two- 
ported memory; four 
2 56KTP cards are required 
to take advantage of the full 
1024- by 1024-pixel, 2 56- 
color capability of the S- 
Series. The SDCM Color 
Modulator Board converts 
red-green-blue signals to 
broadcast-type composite 



signals meeting either the 
NTSC or PAL standards. 

The S-Series cards allow 
computer-generated or 
digitized graphics to be 
overlaid on other broadcast 
images. A zoom feature 
allows up to 4-to-l enlarge- 
ment of screen areas, while 
a pan feature can be used 



to move through the 1024 
by 1024 image area either 
displaying edges or wrap- 
ping around to the opposite 
side of the image. Image in- 
put and output are possible 
using a wide range of 
devices: Any composite- 
video image can be digi- 
tized by the SDD card, while 
the other cards combine to 
provide output in RGB and 
NTSC and PAL composite- 
video formats. 

The SVID video-generator 
board costs $795, while the 
SDCM modulator card is 
$995. Both are available in 
either NTSC or PAL versions. 
The SDMA controller board 
is $795, and each 2 56KTP 
memory card is $1995. The 
SDD digitizer card, for either 
NTSC or PAL versions, is 
priced at $995. Contact 
Cromemco Inc., 280 Bernar- 
do Ave., POB 7400, Moun- 
tain View, CA 94039, (415) 
964-7400. 
Inquiry 606. 



TI's Arborist, Decision Tree Analysis Software, Supports IBM 



Texas Instruments' Arbor- 
ist, a decision-tree anal- 
ysis software package, runs 
on both the TI Professional 
Computer and IBM's Per- 
sonal Computer. Arborist 
brings quantitative decision- 
making techniques to plan- 
ners using these desktop 
computers. 

In decision-tree analysis, a 
series of multiple chance 
events and possible deci- 
sions is represented by a 
tree structure. If the planner 
can estimate the outcome 
and probability of each in- 
dividual decision or event, 
Arborist can then determine 
the best choice at each 
decision point. 

Arborist is intended 
primarily for people who 
have at least a basic 
understanding of decision- 
tree analysis. It uses a 
graphical display of deci- 



sion-tree structures to aid in 
the decision-making process. 
The program accommodates 
color or monochrome dis- 
plays and the 8087 numeric 
coprocessor. 



Arborist sells for $595. For 
further details, contact Texas 
Instruments Inc.. POB 80963, 
Dallas, TX 75380-9063, (800) 
527-3 500. 
Inquiry 607. 




A decision tree created by TI's Arborist. 



XL/Serve for Macs 

XL/Serve permits the 
Macintosh/XL (formerly 
the Lisa 2/10) to function as 
a disk and print server in an 
AppleTalk Personal Network. 
It lets distributed Macin- 
toshes share disk storage 
and Imagewriter printers. 

XL/Serve includes disk and 
printer software that runs 
concurrently on a host Mac- 
intosh/XL under MacWorks, 
driver software for individual 
Macintoshes, and a backup 
and restore utility. 

You can partition the host 
disk into individual volumes, 
and users can be granted 
read-only or read-write 
status. 

XL/Serve is $200. Contact 
Infosphere Inc., 4730 South- 
west Macadam Ave., Port- 
land, OR 97201, (503) 
226-3515. 
Inquiry 608. 

[continued] 



42 BYTE • APRIL 1985 



Borland Does It Again: 
SuperKey $69.95 



Sure, ProKey™ is a nice little program. But when the people who brought you 

Turbo Pascal and SideKick get serious about keyboard enhancers, you can 

expect the impossible ... and we deliver. 



SuperKey 



ProKey 



ALL FEATURES RESIDENT IN RAM AT ALL TIMES 



RESIDENT PULL-DOWN MACRO EDITOR 



RESIDENT FILE ENCRYPTION 




PROKEY COMPATIBILITY 



DISPLAY PROTECTION 



ABILITY TO IMPORT DATA FROM SCREEN 



m 



YES 

^Tyes 

NO YES 

no Si 



I 'yes 



PULL-DOWN MENU USER INTERFACE 



CONTEXT-SENSITIVE ON-LINE HELP SYSTEM 



DISPLAY-ONLY MACRO CREATION 



ENTRY AND FORMAT CONTROL IN DATA FIELDS 



COMMAND KEYS REDEFINABLE "ON THE FLY" 




Total ProKey compatibility. Every Prokey Macro file may be 
used by SuperKey without change so that you may capitalize on 
all the precious time you've invested. 

Now your PC can keep a secret! SuperKey includes a resident 
file encryption system that uses your password to encrypt and 
decrypt files, even while running other programs. Two different 
encryption modes are offered: 

1. Direct overwrite encryption (which leaves the file size un- 
changed) for complete protection. At no point is a second file 
that could be reconstructed by an intruder generated. Without 
your secret password, no one will ever be able to type out your 
confidential letters again! 

2. COM or EXE file encryption which allows you to encrypt a 
binary file into an ASCII file, transmit it through a phone line as a 
text file and turn it back again into an executable file on the 
target machine (only of course if your correspondent knows the 
secret password!). Now, you will even be able to secretly ex- 
change programs through Public Bulletin Board Systems or 
services such as CompuServe. 

Totally memory resident at all times, gives SuperKey the ability 
to create, edit, save and even recall new or existing macro files 
anytime, even while running another program. 

Pull down macro editor. Finally a sensible way to create, edit, 
change and alter existing macro definitions. Even while using 
another application, a simple keystroke instantly opens a 
wordprocessor-like window where you're allowed to see, 
edit, delete, save and even attach names to an indi- 
vidual macro or file of macros, and 
much mora 



12995 



PRICE 



Sony ProKey! 

Superb software at reasonable prices! 

There is much more to SuperKey. Maybe the best 
reason to buy SuperKey is that it is a Borland 
International Product. Each one of our products is 
the best in its category. We only believe in 
absolutely superb software at reasonable prices! 

An offer you can't refuse. 

Whether you are a ProKey user or you've never used a 
keyboard enhancer before, your boat has come in: until 
June 1st 1985 you can get your copy of SuperKey at this 
special introductory price. 

Get your PC a SuperKey today! 

SuperKey is available now for your IBM PC, XT, AT, jr. and truly 
compatible microcomputers. 



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Inquiry 48 



BORlPflD 

INTERNATIONAL 



Software's Newest Direction 

4113 Scons Valley Dave 
Scoits Valley. California 95066 
TELEX 172373 



\ 
\ 

\ 



IBM is a registered trademark of International Business Machine Corporation. ProKey is a trademark 
of RoseSoft. SuperKey and SideKick are trademarks of Borland International, Inc. 





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WHAT'S NEW 



Hayes Offers Smartcom II for the Macintosh 



Hayes Microcomputer 
Products has an- 
nounced Smartcom II for 
the Macintosh. The program, 
originally written for the 
IBM PC, has been rede- 
signed to take advantage of 
the Macintosh graphical user 
interface. 

Smartcom II is compatible 
with Hayes's existing stand- 
alone modems and with its 
recently introduced 2400- 
bps Smartmodem. Smart- 
com II can handle com- 
munications between com- 
puters in a hard-wired con- 
figuration at speeds of up to 
19,200 bps. 

Smartcom II has an "auto- 
pilot" feature that can be 
programmed to automatical- 
ly perform such functions as 
logging onto remote sys- 
tems, sending or receiving 



<ft File (dM Connection Settings HutopHot Special 




•w 



Inter phone number: 



9523083 



00 Q Tone puis * 

€H00 p8U$e Q] seconds 

CD (3d) (E} Wait for dtoMone 

000 !}u ' e, Fl8sh 




Smartcom II exploits the Mac's graphical user interface. 

files, and performing data- Protocol and the XMODEM 

base operations. It supports protocol for file transfers. It 
both the Hayes Verification also lets you switch back 



and forth between voice and 
data during a communica- 
tions session. 

Hayes reports that the 
Smartcom II program will 
permit two Macintosh com- 
puters to exchange graphical 
images in real time using 
conventions similar to those 
in MacPaint. An image 
created on one screen is 
automatically reproduced on 
the remote screen. The sec- 
ond user can "take over" 
the drawing and make 
changes and additions. 

The retail price for the 
Smartcom II software for the 
Macintosh is $149. For more 
information, contact Hayes 
Microcomputer Products 
Inc. 5923 Peachtree In- 
dustrial Blvd., Norcross, GA 
30092, (404) 449-8791. 
Inquiry 609. 



Multiuser Board for IBM Based on 68000 



The Multi-PC/68 from 
LinkData is a multiuser 
68000 microprocessor board 
for the IBM Personal Com- 
puter. This two-board com- 
bination runs UNI-DOS, a 
DEC-like operating system 
that lets the PC run multi- 
user software written for the 
DEC PDP-11 family of mini- 
computers. 



When equipped with 
Multi-PC/68, the IBM PC XT 
can support four terminals 
and run five concurrent pro- 
grams written in the DIBOL 
or CADOL minicomputer 
languages. The IBM PC AT 
can support up to eight ter- 
minals and run nine pro- 
grams. In addition, both the 
XT and AT can run MS-DOS 



applications concurrently 
with UNI-DOS applications. 

The dealer price of the 
Multi-PC/68 system, including 
UNI-DOS, ranges from 
$2000 to $4000, depending 
on how much memory and 
how many RS-232C ports 
are included. LinkData will 
also make available to 
dealers a $200 DEC-like 



word processor, a series of 
accounting packages ($295 
each), and a line of vertical- 
market applications pack- 
ages with price tags span- 
ning from $750 to $1000. 
For more information, con- 
tact LinkData, 2005 Route 
22, Union, NJ 07083, (201) 
964-6090. 
Inquiry 610. 



Harmony Comes to Mac 



Harris Announces PC Network/File Server 



Harmony is a set of 
productivity tools that 
runs as a desk accessory on 
the 512K-byte Macintosh or 
as an application program 
on the 128K-byte Macintosh, 
Harmony offers a full data- 
base in which each record 
can hold up to 18 informa- 
tion fields. Harmony has a 
time-manager module with a 
calendar, an appointment 
book with project-manage- 
ment features, a memo 
writer, and a print-spooler 
application that spools files 
from MacWrite and Micro- 



soft Word. 

Other features include a 
telecommunications applica- 
tion with auto-dial capabili- 
ties. Harmony can work in 
concert with Jazz from Lotus 
Development Corporation 
and other Macintosh pro- 
grams. Intermatrix says that 
the program will be avail- 
able in mid-April and that it 
will be priced at $195. Con- 
tact Intermatrix, 5 547 
Satsuma Ave, North 
Hollywood, CA 91601, (818) 
509-0474. 
Inquiry 611. 



The Harris 9300 net- 
work/file server can link 
up to 16 IBM PC-compati- 
bles, 3270 terminals, Harris 
PCs, or printers with a high- 
capacity hard-disk drive and 
a local-area network. 

Devices are linked by a 
coaxial cable with a data- 
flow rate of 1 megabit per 
second. The 9300 uses an 
80286 chip for network pro- 
cessing and supports up to 
80 megabytes of hard-disk 
storage and 2 megabytes of 
memory An optional Z80B 
runs word-processor and 



office-automation programs 
developed by Lanier, a sub- 
sidiary of Harris. 

The system with 1 mega- 
byte of memory, 37 mega- 
bytes of hard-disk storage, 
and hardware for connection 
to the network is about 
$11,000. Adapter cards for 
personal computers are 
$1050 each. Deliveries are 
expected to begin in June. 
Contact Harris Corp., 
Melbourne, FL 32919, (305) 
727-9100. 
Inquiry 612. 

(continued on page 440) 



44 B YTE • APRIL 1985 



Speed, Power, Price. 
3or land's Turbo Pascal Family. 



Tfie industry Standard. With more than 250,000 users worldwide Turbo Pascal is the industry's de facto standard 
Turbo Pascal is praised by more engineers, hobbyists, students and professional programmers than any other development 
environment in the history of microcomputing. And yet, Turbo Pascal is simple and fun to use! 

Jeff Duntemann. PC Magazine: "Language deal of the century . . . Turbo Pascal: It introduces a new 
programming environment and runs like magic. " 

Dave Garland, Popular Computing: "Most Pascal compilers barely fit on a disk, but Turbo Pascal packs an editor, compiler, linker, 
and run-time library into just 29K bytes of random-access memory" 

Jerry Pournelle, BYTE: "What I think the computer industry is headed for: well documented, standard, plenty of good features, 
and a reasonable price. " 

Portability Turbo Pascal is available today for most computers running PC DOS, MS DOS, CP/M 80 or CP/M 86. A XENIX verison of Turbo 
Pascal will soon be announced, and before the end of the year, Turbo Pascal will be running on most 68000 based microcomputers. 





High resolution monochrome graphics for the IBM PC and the Zenith 100 computers 



Dazzling 

the expert's 




graphics and painless WindOWS. The Turbo Graphix Toolbox will give even a beginning programmer 

s a complete library of Pascal procedures that include: 

Full graphics window management. 

—Tools that will allow you to draw and hatch pie charts, bar charts, circles, rectangles and a full range of geometric shapes. 
Procedures that will save and restore graphic images to and from disk. 
—Functions that will allow you to precisely plot curves. 

—Tools that will allow you to create animation or solve those difficult curve fitting problems, 
and much, much more ..... 

No Sweat and no royalties. You may incorporate part, or all of these tools in your programs, 
and yet, we won't charge you any royalties. Best of all, these functions and procedures come complete 
with commented source code on disk ready to compile! 





Searching and sorting made simple 

The perfect Complement tO Turbo Pascal. It contains: Turbo-Access, a powerful implementation of the state-of-the-art B+tree ISAM 
technique; Turbo-Sort, a super efficient implementation of the fastest data sorting algorithm, "Quicksort on disk". And much more. 

Jerty Pournelle, BYTE: The tools include a B+tree search and a sorting system, I've seen stuff like this, but not 
as well thought out, sell for hundreds of dollars," 

Get Started right away: free database! Included on every Toolbox disk is the source code to a working 
data base which demonstrates how powerful and easy to use the Turbo-Access system really is. 
Modify it to suit your individual needs or just compile it and run. 

Remember, no royalties! 





From Start to finish in 300 pages. Turbo Tutor 

is for everyone, from novice to expert. Even if you've never 
programmed before, Turbo Tutor will get you started right away 
If you already have some experience with Pascal or another 
programming language. Turbo Tutor will take you step by step 
through topics like data structures and pointers. If you're an expert, 
you'll love the sections detailing subjects such as "how to use assem- 
bly language routines with your Turbo Pascal programs." 

A must. You'll find the source code for all 
the examples in the book on the accompanying 
disk ready to compile. Turbo Tutor might be 
the only reference on Pascal and pro- 
gramming you 





nearest V° a 

Mine is: — -pC-DOS -~~ C p/M 8b 

, use. -grfWjjS*.- 



J 54.95 — -" 

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BORlAflD 

INTERNATIONAL 



Ttirfco Pascal is a repstered trademark of BoriantJ international. Inc. 




* 



Introducing PC software 
the right way to do 



IBM's new Personal Decision Series. 
A powerful team of business 
programs designed for exceptional 
flexibility. 

There's rarely one best way of doing 
anything. 

Rather, lots of very good ways: a 
reality that IBM's Personal Decision 
Series handily accommodates. 

More than any software we know of. 
it gives you choices. \bu tailor it to your 



needs, instead of vice versa. 

You begin with Data Edition, a pro- 
gram that not only manages huge 
amounts of information, but letsyou take 
it from a surprising variety of sources: 
data banks, mainframes, even files cre- 
ated by other 1 IX 1 programs. 

And you can retrieve your data in 
nearly an\ form you like, without a lot of 
headscratdiing. You can begin produc- 
ing real work in a couple of hours. 

Add Report s+ and \ou can create 



your- own style documents, pulling facts 
from up to 6 Data files at a time, in 
formats you can design, for applications 
you can invent. 

Graphs gives you a choice of 13 
graph styles, with over 20 variations. 
And you can update old graphs without 



Data 



Reports* 






IBM 



IBM 



With IBMs ne* Personal Decision Series. 
\(iij start toith Data Edition, adding others, like 
Reports* or f'fatis. as yon like. 

For even more help, you can add Apnoint- 



46 BYTE 



APRIL 1985 




based on the curious notion that 
thi ngs is any way you want to. 



having to make new ones. 

There's also Plans + for financial 
modeling and spreadsheets, and Words 
for putting your sentences, numbers and 
graphs all together. 

The Personal Decision Series can 
even take information from a number of 



- 



Graphs 



Pians+ 









IBM 



meni Calendar, Client Time/Cost Accounting, and 
Prospect 1 racking Editions. 

Also, tlic Personal Decision Series works 
wit li data from IBM's new Business Management 



non-Series programs. So if you already 
have a favorite spreadsheet or writing 
program, you ma\ still be able to use it. 

You can even use files from an IBM 
System/36 or- System/370 computer; by 
adding an Attachment I'M) or /'A70 Edition. 

All of which is perfect for* people 




Series, a powerful fainih of accounting programs. 
And ask about IBM Kxtended Support ser- 
vices, a wa> to^et software updates and telephone 
assistance direct from IBM. 



who insist on doing tilings their way. 
Do you know somebody like that'/ 
lb learn more, call an IBM market- 
ing representative, or visit an IBM Pro- 
duct Center or authorized IBM PC dealer. 
For the store nearest vou. and a free 
brochure, call 800- -147- 4700. (In Alaska 
and Hawaii. 800-447-0890.) 



Personal ( Computer Software 



Little Tramp character licensed by Bubbles Inc., s.a. 
Inquiry 194 



APRIL 1985 -BYTE 47 



ASK BYTE 



Conducted by Steve Ciarcia 



Elementary Information 

Dear Steve, 

Can you tell me where I can get specific 
and in-depth answers to elementary ques- 
tions about computers and electronics? I 
know that you answer questions, but I also 
know that you couldn't be expected to 
give very lengthy answers to my beginner's 
questions. 

Charles F. Porter 
Cedar Rapids, I A 

The Ask BYTE column addresses hard- 
ware-related questions of general interest 
but is not meant for the beginner. BYTE's 
sister publication, Popular Computing, 
caters to a less technical audience, and 
its Ask Popular column addresses ques- 
tions related to computers in general. 
Both publications may answer your 
specific question, but the turnaround 
time is lengthy. 

If you need specific answers to specific 
questions in a reasonable amount of 
time, try a local computer club There is 
usually an "expert' available on almost 
any topic. Failing that, the local bookstore 
will feature many books on computers 
and computer-related material.— Steve 



S-100 Switching Supply 

Dear Steve, 

Will you be doing an article on a switch- 
ing power supply for the S-100 bus? 

I hear that switching supplies are less ex- 
pensive to build than linear supplies; the 
selling prices 1 have seen are not less. 
Could Micromint offer a power-supply kit 
for this purpose? 

Ernest A. Knipp 
Houston, TX 

A switching power supply for S-100- 
type computers is a good idea, and I will 
consider it for a future article. 

The cost of switching-type power sup- 
plies is usually less than linear-regulated 
supplies of comparable power because 
smaller capacitors and inductors are used 
and can be packaged in a smaller 
volume. They also generate less heat and 
are easier to cool, resulting in a lower 



overall installed cost. 

If you want to build your own switch- 
ing supply my article in the November 
1981 BYTE provides the basics. "Switch- 
ing Power Supplies: An Introduction'' 
covers the fundamentals of design and 
describes a workable unit This article 
isn 't a do-it-yourself S-100 power-supply 
project, but it should give you most of the 
basics. 

Several ± 12-V, 5-V switching supplies 
are available commercially, including the 
MPX-IO (from Micromint 561 Willow Ave. 
Cedar hurst, NY II 51 6), which powers the 
MPX-16 computer. Others are available 
from Kepco Inc., 131-38 San ford Ave., 
Flushing, NY H352; Lambda Electronics, 
515 Broad Hollow Rd., Melville, NY 
1 1 74 7: and Sorensen, 6 76 Island Pond 
Rd., Manchester, NH 03103 .—Steve 



Graphic-Arts Computer 

Dear Steve, 

1 would like to do graphic-arts work with 
a computer capable of producing a 
minimum of about 800 by 800 pixels and 
at least 100 simultaneously displayable 
colors. I have seen ads for various color 
boards or dedicated graphics computers, 
but they either don't match my specs or 
they are too expensive. 

I'd like to build my own color add-on 
board for the Commodore 64 or a com- 
plete computer. I'd appreciate any 
suggestions. 

Les Kohuth 
Syosset, NY 

High-resolution graphics systems are 
expensive and seem overpriced in com- 
parison to the graphics systems available 
on microcomputers. To understand this 
high cost, let's look at the components 
of a high-resolution graphics system. 

To display the resolution that you men- 
tioned, a monitor with a video band- 
width of at least 1 8 to 20 MHz is needed 
to distinguish individual pixels, or dots. 
This requirement can be understood if 
we look at the makeup of one scan line 
of the picture. 

The normal scan rate is 15,750 scans 
per second, and at 800 pixels of hori- 



zontal resolution, this is 1 2,600,000 pixels 
per second. However, the case where all 
the pixels are lit results in a zero-band- 
width requirement, and a DC voltage is 
all that is required. In the worst case, 
when every other pixel is lit, a clear dis- 
play of 6 million pixels per second is 
needed. This appears to require only a 
6-MHz bandwidth, but bandwidth is 
usually defined as the frequency where 
the signal (or gain) is reduced by 3 dB, 
or 50 percent of the normal level. Such 
a bandwidth would result in low bright- 
ness and contrast in picture areas where 
fine detail is shown. To display sharp im- 
ages at this resolution, it is necessary to 
approximate a square wave at 6 MHz, 
and the first component of a square wave 
above the fundamental is the third har- 
monic, or 18 MHz. This is the minimum 
acceptable, and a noticeable improve- 
ment should be seen if the bandwidth is 
extended to the next component, which 
is the fifth harmonic (30 MHz). 

The standard television sweep frequen- 
cies generate 525 horizontal lines per 
frame in two vertical scans (interlaced). 
A limit of about 400 lines within this 
region is required for good linearity. Most 
microcomputer graphics systems provide 
200 or so lines by using the so-called 
noninterlace mode, displaying the same 
information on adjacent pairs of lines. 
This can be doubled by using twice as 
much memory and reprogramming the 
video controller. Getting to 800 lines re- 
quires twice as many horizontal sweeps 
per frame (and half the frame rate), which 
is not within the capabilities of the 
popular $500 RGB monitors. Monitors of 
this type are available, but the prices are 
in the several-thousand-dollar range. 

800 by 800 pixels requires 640K bits, 
or about 80K bytes, of memory to give 
one color (we get black for free). If you 
want to be able to assign different colors 
to each pixel, rather than define charac- 
ters within a block of 8 by 8 contiguous 
pixels, the memory is arranged in layers. 
One 80K-byte layer gives black and white, 
two layers doubles this to four colors 
(three colors plus black), another layer 
doubles again, etc., for as many colors 
as we want, or can afford. Your spec of 

{continued) 



48 BYTE • APRIL 1985 



COPYRIGHT© 1985 STEVEN A. CIARCIA. ALL RIGHTS RESERVED. 







lector's item— an originally 
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For the name of the 
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APRIL 1985 'BYTE 49 



Inquiry 2 79 




IEEE-488 Interfaces and 
Bus Extenders For: 

IBM PC, PCjr 
& COMPATIBLES 

DEC UNIBUS, Q-BUS 
& RAINBOW 100 

MULTIBUS, VMEbus 
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trademarks of Digital Equipment Corporation 



ASK BYTE 



"at least IOO colors" rounds up to 128, 
or seven layers of memory. This is $700 
worth of memory chips, if you can use 
the low-cost 64K-byte chips in common 
use for microcomputer memory these 
days. Add board space and sockets and 
do the work yourself, and you're still talk- 
ing $1000 for memory and this type of 
memory really isn't suitable for a high- 
performance graphics board. You really 
need a two-port system so that putting 
data into the memory doesn't interfere 
with the display and vice versa. 

This amount of memory exceeds the 
addressing capacity of all the common 
video-controller chips. Also, 6 million 
pixels must be read from memory each 
second. At 7 bits per pixel, the processor 
must access 7 5 OK bytes from each layer 
each second, or a total of 5.25 mega- 
bytes per second throughput if only one 
processor is used. This is too fast for in- 
expensive video processors, or micropro- 
cessors, so either parallel or very fast 
processors with bank switching are 
needed. Such circuitry is complicated, 
and considerable processing is required 
to separate the data into the required 
RGB analog signals. 

Some boards, or add-on systems, are 
available for the IBM PC and some of its 
clones that can provide various combina- 
tions of features at reasonable cost One 
such system is the VX, made by Vectrix 
Corporation, 1416 Boston Rd., Greens- 
boro, NC 27407. This appears to require 
a special monitor, however 

Other systems that are compatible with 
common RGB monitors and provide up 
to 16 colors at 640- by 400-pixel resolu- 
tion and 132 colors at 320 by 200 resolu- 
tion are available from $300 to around 
$1000. Check advertisements for prod- 
ucts made by Qua dram, Princeton 
Graphics, and Tecmar Inc. in magazines 
like BYTE to find some that might repre- 
sent a satisfactory compromise. Another 
good source for information on this sub- 
ject is Electronic Imaging magazine. 
—Steve 



Reconfiguring the PC XT 

Dear Steve. 

I have two questions that I would like to 
have answers for. They both relate to the 
IBM PC XT. After devouring your most in- 
teresting articles and answers in BYTE. I 
believe you can answer them. 

The XT comes equipped with an asyn- 
chronous communications card con- 
figured as COM1. 1 have installed a Hayes 



internal modem that for compatibility with 
some important software I have to use as 
COM! . I have had to remove the IBM asyn- 
chronous card because I don't know how 
to reconfigure it to be COM2. There are 
no switches on it or any documentation 
on how this might be done. I have been 
told that it is possible, but no one has 
been able to tell me how to do it. 

There are times when I really don't need 
to use my hard disk, such as when I am 
working for hours on a mainframe and just 
using my XT as a terminal. Since my war- 
ranty has expired anyway I don't mind ex- 
perimenting if I have some expert 
guidance. Would there be any way to boot 
my system without the hard disk, when it 
is not needed, by installing a switch some- 
place? If this is possible, would it be worth 
saving a few hours of idle running time on 
the hard disk? 1 know it would be quieter 
and more enjoyable working without it 
when I don't need it. 

Bob Stephan 
Pebble Beach, CA 

Modifying the IBM asynchronous card 
to make it operate as COM2 is feasible. 
The port addresses used by COM I are 
3F8H to 3FFH. while COM2 uses 2F8H 
to 2FFH. The schematic in the IBM PC 
Technical Reference Manual shows a 
jumper that determines whether the card 
is selected with A8 equal to or 1, al- 
though neither the documentation that 
comes with the card nor the Technical 
Reference Manual makes reference to 
this. The jumper is probably soldered in 
and may not be there on all boards. 

Modifying the main system board to 
start up without the fixed disk is an 
operation I don't recommend. The in- 
crease in life of the fixed disk is probably 
minimal, and turning it on and off when 
you need it might offset any gain realized 
by not running it full time. 1 also suspect, 
based on my experience with IBM PCs, 
that the fan makes as much noise as the 
disk, so there is little to be gained—Steve 



Reading Latch Outputs 

Dear Steve, 

I have a Sinclair 1000 that I'm trying to 
use in a security system. In my system, 
octal latches monitor infrared beams. 
When a beam is broken, my program ad- 
dresses a latch at an address above RAM 
and uses a POKE to put a 1 in the latch 
to ring the bell. This works fine. The prob- 
lem is when 1 try to check the octal latches 

(continued) 



50 



BYTE* APRIL 1985 



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But now there's a solution you can af- 
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And when the AC line fails, the SPS goes into full 

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with the PEEK command, instead of see- 
ing the latch, it reads garbage. 1 have tried 
addresses just above RAM all the way up 
to address 65535. and 1 still read garbage. 
It appears that when you check an ad- 
dress that is above RAM it mirrors back 
to a RAM or ROM address. Can you tell 
me how I can address and see my octal 
latches instead of mirroring back to RAM? 
Thanks for your help. 

Dan Grogan 
San Pedro, CA 

It appears that your Sinclair 1000 is not 
reflecting your PEEK commands back 
into low memory As I interpret your let- 
ter you have a set of latches that are sup- 
posed to put data on the bus to tell the 
computer that a detector has been 
tripped, and you are having trouble 
reading the latch outputs. 

Are you sure that the address decoder 
on the latch board is set to the address 
to which you are writing? Is it properly 
timed to put the data on the bus at the 
right time or hold it there long enough 
to be recognized by the processor? The 
fact that you can write a bit into the bell 
latch seems to indicate that you are able 
to address the high memory, but the tim- 
ing in writing data into the latch could be 
a lot less critical than reading data. 

Have you looked at the signals at the 
latch outputs and on the data bus to be 
sure that they are putting out the correct 
voltage levels? How about signal quali- 
ty? The level is fairly easy to get with TTL 
or CMOS chips if the power-supply volt- 
age is at the required 5 volts, but if the 
wiring connecting the latches to the com- 
puter bus isn't properly dressed, you can 
do horrible things to the normally clean 
square waves put out by the latches. 
—Steve 



A/D FOR Z- 100 



Dear Steve, 

I have a Zenith Z-100 computer with two 
disk drives and with 192K bytes of 
memory. Now I am thinking of providing 
an A/D interface for the serial input so that 
I can feed in analog signals from various 
instruments, such as a spectrophotometer 
pH meter, etc Looking through the jour- 
nals 1 located a few suppliers, though 
mostly of rather fancy multichannel data- 
acquisition units I do not need. At the 
most, 1 need four channels of input with- 
out any specialties attached. I would ap- 
preciate it if you could let me know of any 

[continued) 



52 BYTE • APRIL 1985 



Inquiry 353 




viztec The Most Powerful C 



for the IBM AT • MACINTOSH • MS DOS • CP/M-80 • ROM APPLICATIONS 
IBM PC/XT • APPLE // • CP/M-86 • TRSDOS • CROSS DEVELOPMENT 



Why Professionals Choose Aztec C 

AZTEC C compilers generate fast, compact 
code. AZTEC C is a sophisticated development 
system with assemblers, debuggers, linkers, 
editors, utilities and extensive run time libraries. 
AZTEC C is documented in detail. AZTEC C is 
the most accurate and portable implementation 
of C for microcomputers. AZTEC C supports 
specialized professional needs such as cross 
development and ROM code development. 
MANX provides qualified technical support. 

AZTEC C86/PRO 
— for the IBM AT and PC/XT 

AZTEC C86/PRO provides the power, portabili- 
ty, and professional features you need to 
develop sophisticated software for PC DOS, MS 
DOS AND CP/M-86 based microsystems. The 
system also supports the generation of ROM 
based software for 8088/8086, 80186, and 80286 
processors. Options exist to cross develop ROM 
code for 65xx, 8080, 8085, and Z80 processors. 
Cross development systems are also available 
that target most micro computers. Call for infor- 
mation on AZTEC C86/PRO support for XENIX 
andTOPVIEW. 



POWERFUL - AZTEC C86/PRO 3.2 outper- 
forms Lattice 2.1 on the DHRYSTONE 
benchmark 2 to 1 for speed (17.8 sees vs 37.1) 
while using 65% less memory (5.8k vs 14k). The 
AZTEC C86/PRO system also compiles in 10% 
to 60% less time and supports fast, high volume 
I/O. 



PORTABLE — MANX Software Systems pro- 
vides real portability with a family of compatible 
AZTEC C software development systems for PC 
DOS, MS DOS, CP/M-86, Macintosh, CP/M-80, 
APPLE //+ , //e, and //c (NIBBLE - 4 apple rating), 
TRSDOS (80-MICRO - 5 star rating), and Commo- 
dore C64 (the C64 system is only available as a 
cross compiler - call for details). AZTEC 
C86/PRO is compatible with UNIX and XENIX. 



PROFESSIONAL — For professional features 
AZTEC C86/PRO is unparalleled. 

• Full C Compiler (8088/8086 - 80186 - 80286) 

• Macro Assembler for 8088/8086/80186/80286 

• Linkage Editor with ROM support and overlays 

• Run Time Libraries - object libraries + source 
DOS 1.x; DOS 2.x; DOS 3.x; screen I/O; Graphics; 
UNIX I/O; STRING; simulated float; 8087 support; 
MATH; ROM; CP/M-86 

• Selection of 8088/8086, 80186, or 80286 code genera- 
tion to guarantee best choice for performance and 
compatibility 



• Utility to convert AZTEC object code or libraries to 
Microsoft format. (Assembly + conversion takes 
less than half the time as Microsoft's MASM to pro- 
duce MS object) 

• Large memory models and sophisticated memory 
management 

• Support products for graphics, DB, Screen, & ... 

• ROMable code + ROM support + separate code and 
data + INTEL Hex Converter 

• Symbolic Debugger & Other Utilities 

• Full Screen Editor (like Vi) 

• CROSS Compilers are available to APPLE //, Macin- 
tosh, CP/M-80, TRSDOS, COMMODORE C64, and 
ROM based 65xx, and 8080/8085/Z80 

• Detailed Documentation 

AZTEC C86/PRO-AT $500 

(configured for IBM AT - options for 8088/8086) 

AZTEC C86/PRO-PC/XT $500 

(configured for IBM PC/XT - options for 80186/80286) 

AZTEC C86/BAS includes C compiler (small model only), 
8086 MACRO assembler, overlay linker, UNIX, MATH, 
SCREEN, and GRAPHICS libraries, debugger, and 
editor. 

AZTEC C86/BAS $199 

AZTEC C86/BAS (CP/M-86) $199 

AZTEC C86/BAS (DOS + CP/M-86) $299 

UPGRADE to AZTEC C86/PRO $310 

CTREE Database with source .$399 

CTREE Database (object) $149 

CROSS COMPILERS 
Cross Compilers for ROM, MS DOS, PC DOS, or CP/M-86 
applications. 

VAX - > 8086/80xxx cross $5000 

PDP-1 1 - > 8086/80XXX cross $2000 

Cross Compilers with PC DOS or CP/M-86 hosts are $750 
for the first target and $500 for each additional target. 
Targets: 65xx; CP/M-80; C64; 8080/8085 /Z80; Macintosh; 
TRSDOS; 8086/8088/80186/80286; APPLE //. 



AZTEC C68K 

— for the Macintosh 

For power, portability, and professional features 
AZTEC C68K-C is the finest C software development 
system available for the Macintosh. 

The AZTEC C68K-C system includes a 66000 macro 
assembler, a linkage editor, a source editor, a mouse 
based editor, a SHELL development environment, a 
library of UNIX I/O and utility routines, full access and 
support of the Macintosh TOOLBOX routines, debug- 
ging aides, utilities, make, diff, grep, TTY simulator with 
upload & download (source supplied), a RAM disk (for 
51 2K Mac), a resource maker, and a no royalty license 
agreement. Programming examples are included. (Over 
600 pages of documentation). 

AZTEC C68K-C requires a 128K Macintosh, 
and two disk drives (frugal developers can make 
do with one drive). AZTEC C68K supports the 
512K Macintosh and hard disks. 

AZTEC C68K-C (commercial system) $500 

AZTEC C68K-p (personal system) $199 

AZTEC C68K-p to AZTEC C68K-C upgrade $310 



Mac C-tree database $149 

Mac C-tree database with source $399 

Lisa Kit (Pascal to AZTEC C68k object converter) . . $ 99 



AZTEC C65 

"...The AZTEC C-system is one of the finest software 
packages i have seen..." NIBBLE review, July 1984. 

The only commercial C development system available 
that runs native on the APPLE II + , lie, and lie, the 
AZTEC C65 development system includes a full floating 
point C compiler compatible with UNIX C and other 
MANX AZTEC C compilers, a 6502 relocating assem- 
bler, a linkage editor, a library utility, a SHELL develop- 
ment environment, a full screen editor, UNIX I/O and 
utility subroutines, simple graphics, and screen func- 
tions. 

AZTEC C65 (Apple DOS 3.3) $199 

AZTEC C65/PRO (Apple DOS + ProDos) $350 

(call for availability) 



AZTEC C ll/PRO 

— for CP/M-80 

The first member of the AZTEC C family was the 
CP/M-80 AZTEC C compiler. It is "the standard" com- 
piler for development on CP/M-80. The system includes 
the AZTEC CMC compiler, an 8080 assembler, a linkage 
editor, an object librarian, a full library of UNIX I/O and 
utility routines, CP/M-80 run time routines, the SMALL 
library (creates modules less than 3K in size), the fast 
linker for reduced development times, the ROM library, 
RMAC and M80 support, library source, support for 
DRI's SID/ZSID symbolic debugger, and more. 

AZTEC C ll/PRO $349 

AZTEC Cli/BAS $199 

CTREE Database with source $399 

CTREE Database in AZTEC object form .$149 



AZTEC C80 

— for TRSDOS (Radio Shack Model III & 4) 

'7 Ve had a lot of experience with different C compilers, 
but the Aztec C80 Compiler and Professional Develop- 
ment System is the best I've seen." 80-Micro, Decem- 
ber, 1984, John B. Harrell III 

This sytem has most of the features of AZTEC C II for 
CP/M. It is perhaps the best software development 
system for the Radio Shack Model III and IV. 

AZTEC C80 model 3 (no floating point) $149 

AZTEC C80 model 4 (full) $199 

AZTEC C80/PRO (full for model 3 and 4) $299 



.11 



1-221-0440 

(201) 530-7997 (NJ and outside U.S.A.). Or write: MANX 
SOFTWARE SYSTEMS, P.O. Box 55, Shrewsbury, N.J. 
07701 



MANX 

TRS 80 RADIO SHACK TRS DOS is a trademark of TANDY 
APPLE DOS MACINTOSH is a trademark of APPLE. 




SHIPPING INFORMATION - Standard U.S. 
shipment is UPS ground {no fee). In the U.S. 
one day shipment is $20, two days is $10. 
Canadian shipment is $10. Two days ship- 
ment outside the U.S. is by courier and is 
freight collect. 



For Technical Support 
(Bug Busters) call: 201-530-6557 



Inquiry 247 



APRIL 1985 -BYTE 53 




ASK BYTE 



CLEAN THE MACHINE! 



There's enough to worry about without 
the headache of your computer's down- 
time or the loss of valuable data caused 
by dust. 

Before dust affects your computer's 
operation do what a rapidly growing 
number of computer users do: use Dust- 
Off® II. Don't just move dust — remove 



STAT-OFF IF 
neutralizes 
dust- holding 
static electricity 
from media and 
machines. 



it. Unlike liquid cleaners, Dust-Off II is a 
safe, dry "canned air" cleaning system 
for your computers, printers, disk and 
tape drives, diskettes, CRTs, media 
storage containers and modems. In 
fact, it works on everything that works 
in the office. 

Dust-Off II's patented valve gives 
you pinpoint fingertip-control to blast 
away pollutants before they cause 
aggravating downtime. Add the Stat- 
Off® II accessory, and you have the only 
dry, non-contact method for eliminating 



dust-holding static electricity. The Dust- 
Off II system also includes the Dual Ex- 
tender and the Mini-Vac vacuum for 
eliminating hard-to-reach dust. 

Get Dust-Off II at your local com- 
puter or office supply dealer. Or send 
$1.00 {postage and handling) for a 3 oz. 
trial size and literature. 





DustOffll 

THE SAFE, DRY, "CANNED AIR"CIEANING SYSTEM. 



such units on the market. 

Herbert Jonas 
St. Paul, MN 

Analog Devices (2 Technology Way, 
Norwood. MA 02062, (617) 329-4700} 
makes the /iMAC-4000 series data-acqui- 
sition systems that provide up to 12 chan- 
nels of 1 3 -bit A/D input/output and serial 
communication, priced at $995 and up. 

Two other units that interface through 
RS-232Carethe 16<hannel, 12-bit ADC-I 
from Remote Measurement Systems Inc., 
POB 15544, Seattle, WA 98115, (206) 
525-3369. It's advertised at $369. Also 
available is the BUSSter D16 8-bit, 
16-channel unit from Connecticut micro- 
Computer The address is 36 Del Mar Dr., 
Brookfield, CT 06804, (203) 775-4595. 

All three of the above units accept 
digital inputs as well as analog. 

Since your Z-100 uses the S-100 bus, 
you might also want to consider the plug- 
in AIM-12 S-100 board from Dual Sys- 
tems Corp.. 2530 San Pablo Ave., 
Berkeley. CA 94702, (415) 549-3854. This 
unit provides for 16 channels of input 
with 12-bit conversion, priced at $775. 
—Steve ■ 

Between Circuit Cellar Feedback, personal ques- 
tions, and Ask BYTE, I receive hundreds of letters 
each month. As you might have noticed, at the end 
of Ask BYTE I have listed my own paid staff. We 
answer many more letters than you see published. 
and it often takes a lot of research. 

\f you would like to share the knowledge you have 
on microcomputer hardware with other BYTE 
readers, joining the Circuit Cellar! Ask BYTE staff 
would give you the opportunity. Wre looking for 
additional researchers to answer letters and gather 
Circuit Cellar project material. 

\f you're interested, let us hear from you. Send 
a short letter describing your areas of interest and 
qualifications to Steve Garcia, POB 582, Glaston- 
bury, CT 06033. 



IN ASK BYTE, Steve Garcia answers questions 
on any area of microcomputing. The most rep- 
resentative questions received each month will be 
answered and published. Do you have a nag- 
ging problem? Send your inquiry to 

Ask BYTE 

do Steve Ciarcia 

POB 582 

Glastonbury, CT 06033 
Due to the high volume of inquiries, personal 
replies cannot be given. All letters and photo- 
graphs become the property of Steve Ciarcia and 
cannot be returned. Be sure to include "Ask 
BYTE" in the address. 

The Ask BYTE staff includes manager Harv 
Werner and researchers Bill Curlew, Larry 
Bregoli. Dick Sawyer, and \eannette Dojan. 



Falcon Safety Products, Inc., Dept. B, 1065 Bristol Road, Mountainside, N.J. 07092. U.S.A. 

54 BYTE • APRIL 1985 Inquiry I5I 



Now Showing 
In Black And White 



tf you own an IBM-PC 
or PC work-alike, 
Roland's new MB-142 
monitor lets you show off 
your text and graphics in 
today's hottest colors— 
black and white. That's 
right! The MB-142 gives 
you black characters on a 
paper-white background- 
just like people have been 
reading for centuries. You 
can also have white char- 
acters on a black back- 
ground with just the touch 
of a button. 

Both of these black and 
white display formats are 
easier on the eyes and 
less fatiguing than the green 
or amber phosphor used in 
standard monochrome 
monitors. The MB-142's 
large 14-inch screen, com- 
bined with its ultra-high 
720 x 350 resolution, 
can display characters 
that are larger and 
more legible than what 
you can get with ordi- 
nary monochrome 
monitors. Another 
great plus is that the 
MB-142 plugs directly 
into the monochrome 
board of your IBM or com- 
patible—just like your pres- 
ent monochrome monitor, 
with nothing more to buy. 
Because of the MB-142's 
advanced electronic cir- 
cuitry, you even have the 
ability to mix graphics and 
text on the same display 
when using graphics and text 
boards from leading manu- 
facturers such as Persyst, 
STB, Paradise, Hercules, AST 
and many others. What makes 
it all possible? The same 
sophisticated technology 
used in color monitors. 



Inquiry 336 





the MB-142 
supports 
all the 
winning 
cards 



' ush a 
button for 
instant reverse 
screen 




the big difference is 
► that the MB-142 
monitor does the job for 
significantly less money. 
The MB-142 is designed 
to interface economically, 
too. Imagine seeing your 
favorite business graphics 
or CAD/CAM packages, 
such as Lotus 1-2-3, Ener- 
graphics, Chart-Master, 
AutoCAD, CADDraft and 
VersaCAD, in ultra-high 
resolution black and 
white. Also, take full 
advantage of your pro- 
gram's windowing 
capability using the large 
14-inch screen. 
T^ke a good look at the 
differences that set the 
MB-142 apart from the rest. 
No other monochrome 
monitor gives you the 
fatigue-free black and 
white viewing, text and 
graphics capabilities 
and easy interface. 
Naturally enough, 
the MB-142 is from 
Roland DG-the 
new computer 
peripherals company 
that's pointing the way 
to the future. Look for 
this and other Roland 
products at fine com- 
puter dealers 
everywhere. 
For more information, 
contact: Roland DG, 
7200 Dominion Circle, Los 
Angeles, CA 90040. 
(213) 685-5141. 



The software programs listed are trademarks 
of the following companies: AutoCAD. 
AUTODESK, Inc.; CADDraft, Personal CAD 
Systems, Inc.; Chart-Master, Decision 
Resources, Inc.; Energraphics, Enertronic 
Research, Inc.; Lotus 1-2-3, Lotus Develop- 
ment Corp.; VersaCAD. T&W Systems, Inc. 



APRIL 1985 'BYTE 55 



■ 



:i^5^ 



EVEREX. EVER 






M 









I - 







Illllllllllllllll 








Innovative, Highest Quality Products From 



BACKUP SYSTEMS 

Internal 

• Streaming Tape 

• Cassette 

• Floppy Tape 
External 

A selection of Streaming Tape, Cassette and 

Floppy Tape systems in either individual units or 

combined with hard disk drives and expansion 

slots. 

Unique Features: 

• Space-saving half-height infernal systems 

• Backup capacities up to 100 MB 

• Fast image backup-ten megabytes backed 
up in minutes 

• File-by-file and mirror image backup and 
restore 

• EXCLUSIVE file-by-file restore from a fast 
mirror image backup 

• Easy to use software, simply press a key— no 
complex commands 

• Largest selection of backup/ retrieve options 

EXPANSION SYSTEMS 

Everex offers a complete line to choose from . . . 

• Full -Size system with eight expansion slots 
and room to add up to four storage/backup 
systems. 

• Half-Size system with three expansion slots 
and space for two storage/backup systems. 

• Slimline system, only 2 1 2 -inches high with 
three full-size, one half-size expansion slots 
and room for two storage/backup systems. 

• All Expansion systems are available with any 
combination of Everex hard disk drive and 
backup systems. 



Replace the clumsy flat ribbon cable 
with Everex' s shielded, round cable. 




Unique Features: 

• Advanced design eliminates "wait states" 
faster data transmission 

• Highest quality round cables (as IBM) instead 
of flat ribbon cables 

HARD DISK DRIVE SYSTEMS 

Choose from a wide selection of models to meet 
your needs: 

—space-saving internal systems 

-external systems with extra expansion slots 

• Capacities from 10 to 32 megabytes 

• Factory tested for trouble-free operation 

GRAPHICS PRODUCTS 

Everex offers a complete line of graphics 

products to choose from . . . 

The Edge Color/Monochrome adapter 

• Runs color software on your IBM mono- 
chrome display with a FULL SCREEN in 16 
shades, no software patches needed 

• High resolution, 720x348, monochrome 
graphics 

• Operates Lotus 1-2-3, Symphony and other 
popular programs in an extended 132 column 
by 44 or 25 row display in HIGH resolution 
monochrome 

• Printer connection 

Graphics Edge Color/Monochrome adapter 
Similar features as the Edge but also offers: 

• More high resolution colors: 16 in 640x200 
graphics 

















:c 


E 


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U-3C— ** 

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• 



• ■ 

* '% S is -^i "I 

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The Company That Stands For Excellence... 



• Displays the same information on a color AND 
monochrome monitor simultaneously 

Dual Graphics Color/Monochrome adapter 

• Works with high resolution color AND mono- 
chrome displays 

• Operates Lotus 1-2-3, Symphony and other 
popular programs in an extended 132 column 
by 44 or 25 row display 

• More exciting colors: 16 colors in 640x200 
and 320x200 graphics 

• Printer connection 

Graphics Pacer Monochrome adapter and 
Floppy Disk Controller 

• Runs sharp, high resolution monochrome 
graphics 

• Operates up to four floppy disk and floppy 
tape drives 

• Printer connection 

• Uses only one expansion slot 
Evergraphics Monochrome adapter 

• Operates crisp, high resolution monochrome 
graphics 

• Includes printer and light pen connections 

COMMUNICATIONS AND MULTIFUNCTION 

Evercom Internal Modem 

Gives you all of the features found in modems 

costing hundreds more: 

• Fully Hayes and Bell 103/212A compatible 

• Data transmission speeds in either 300 or 
1200 bps 

• Automatic dial and answer 

• Works with tone and pulse phone systems 

• Voice AND data communications 

• Built-in speaker with software volume control 

• Includes powerful, easy to use software 



MagicCard Multifunction adapter 

• Adds more memory to your computer-up to 
384K 

• Serial connection for modems, printers, plot- 
ters and more 

• Printer connection 

• Game paddle/joystick connection 

• Reliable clock/calendar with battery back-up 

• FORM MANAGER electronic filing system and 
form creator 

• PC WRITE easy to use word processing 
program 

• With printer spooler, electronic disk drive and 
more 

Excellence is the standard at Everex-it's in our 
name, our products, in everything we do. When 
you look for the best for your computer-you'll 
find Everex products. 

Visit your local Everex dealer today and ask to 
see Everex products in action. For the name of 
your nearest Everex dealer, please call (415) 
498-1111. 

Dealer Hotline: (800) 821 -0806. In CA (800) 821 -0807. 

Address: 47777 Warm Springs Blvd., Fremont. CA 94539 (415) 498-1111 . 

IBM, PC, XT and AT are registered trademarks of International Business 

Machines Corporation. 

Excel, The Edge, Dual Graphics, Graphics Edge, Graphics Pacer, 

Evergraphics, Evercom and MagicCard are trademarks of Everex 

Systems Inc. 

Form Manager is a trademark of BIT Software Inc. 

PC Write is a trademark of Quicksort Inc. 




EVER for Excellence 

Inquiry 1 46 



CLUBS & NEWSLETTERS 



• FUTURE INTELLIGENCE 

A monthly newsletter 
devoted to tracking future 
computing technologies 
emphasizes research and 
business. Areas covered in- 
clude artificial intelligence, 
supercomputers, parallel 
processing, expert systems, 
natural language, and voice/ 
speech/pattern recognition 
and synthesis. An annual 
subscription is $295. Con- 
tact Ed Rosen f eld, Intelligence. 
POB 20008. New York. NY 
1002 5. 

• BASED IN THE BAY 

A nonprofit users group for 
Sanyo computerists, the Bay 
Area Sanyo Enthusiast 
(BASE) welcomes anyone 
interested in computers. 
Regular meetings are held. 
Contact Lee Swearingen at 
(813) 788-7865 or Dave Rob- 
bins at (813) 886-7751 or 
write BASE, POB 260517. 
Tampa, FL 33685. 

• CHUGGING ALONG 

The Capitol Heath Users 
Group (CHUG) meets on the 
third Monday of every 
month at the Fairfax High 
School in Virginia. Members 
operate two 24-hour bulletin 
boards at (703) 759-2072 
and (703) 360-3812. CHUG 
sponsors an annual con- 
ference, houses special- 
interest groups, and pro- 
duces a monthly newsletter. 
CHUG, which is included in 
the annual $12 membership 
fee. Call John Roach in the 
evening at (703) 971-4930 or 
write CHUG. POB 10515 
Alexandria. VA 22310. 

• STANDARDS BBS 

The National Bureau of 
Standards (NBS) Institute of 
Computer Sciences and 
Technology (1CST) has 



established a BBS at (301) 
948-5718. Open to the 
public, its purpose is to ex- 
change information that 
assists federal agencies in 
the efficient selection of 
software and hardware. 
Among topics discussed are 
security and interfacing. For 
details on the project, con- 
tact Ted Landberg at ICST. 
NBS. 22 5 Room #A266. 
Gaithersburg, MD 20899. 
(301) 921-3485. 

• JOIN CP/M EFFORT 

CP/M S1G assists members 
in the technical aspects of 
CP/M and related software 
through monthly meetings, a 
monthly newsletter, and a 
24-hour RCP/M system at 
(303) 465-1313. Article sub- 
missions are welcome, 
public-domain software is 
available, and lectures 
educate members on areas 
of interest. Discounts on 
hardware and software and 
a subscription to the 
newsletter are provided with 
payment of $12 a year. Con- 
tact CP/M SIG Inc., POB 633, 
Broomfield. CO 80020-0633. 

• GERMAN MAC RULES 

At least once every two 
months, members of Club- 
mac (Europe) submit an 
article to the newsletter on 
anything about the Mac or 
their membership is not 
renewed. The result is a 
newsletter that keeps 
members up to date with 
latest developments, reviews 
new programs and hardware, 
and solves members com- 



puting problems. The annual 
membership fee is £2 5 per 
annum. Contact K. Leslie, 
Clubmac, Triererstrasse 8, 
D-55I1 Wincheringen. West 
Germany. 

• BCS GOES REGIONAL 

The Monadnock Region IBM 
PC Users Group, a subgroup 
of the IBM PC Users Group 
of the Boston Computer 
Society (BCS). gathers in 
Keene, New Hampshire, to 
see demonstrations and 
meet with other users. By 
joining, you benefit from a 
software exchange, group- 
purchase discounts, a 
monthly newsletter, and 
automatic BCS membership 
with access to the BCS BBS. 
Contact Susy Thielen, 4 5 
Kelleher St., Keene, NH 
03431. (603) 352-0971. 

• CALL THE AMATEURS 

The bulletin board of the 
New York Amateur Com- 
puter Club (NYACC) is up 
and running. The bimonthly 
newsletter contains NYC 
users group meetings and 
contacts, a NYACC directory, 
events, articles, letters, and 
news. Meeting times and 
locations of several users 
groups are announced on a 
hotline at (212) 864-4595. 
The membership is $15 an- 
nually; students pay $10. 
Write the NYACC. POB 106. 
Church Street Station, New 
York, NY 10008. 

• DOWN UNDER THE 
TRS-80— Members of the 
Sydney TRS-80 Users Group 



CLUBS & NEWSLETTERS is a forum for letting BYTE readers know what 
is happening in the microcomputing community. Emphasis is given to elec- 
tronic bulletin-board services, club-sponsored classes, community-help projects, 
and other activities. We will continue to list new clubs and newsletters. Allow 
at least four months for your club's mention to appear. Send information 
to BYTE, Clubs & Newsletters. POB 372, Hancock. NH 03449. 



(SYDTRUG) share knowledge 
about hardware, software, 
and education, business, 
and related applications for 
TRS-80 computers. Commu- 
nication occurs through the 
monthly newsletter contain- 
ing news and reviews, plus 
lectures, demonstrations, 
and the 24-hour BBS 
(CLUB-80) in Australia on 
(02) 332-2494. The BBS 
features messages, group 
news, and the exchange of 
public-domain software. 
Meetings are held on the 
second and third Saturdays 
of each month in Botany. 
New South Wales. Write 
SYDTRUG. POB 43, Erskine- 
ville 2043. New South Wales, 
Australia, tei: (02) 772-2009. 

• ENGINEERS ANALYZE 
STRUCTURE-The Structural 
Analysis Programs Associa- 
tion (SAPA) upgrades the 
skills of engineers who use 
microcomputers to analyze 
and design buildings. Struc- 
tural software and computer 
services that address this 
issue are discussed in the 
quarterly newsletter, SAPA 
NEWS, and in seminars held 
one full day in eight-month 
intervals. The annual 
membership fee is $100. 
Contact J. Jeff Davies. SAPA, 
Suite D2. 30 Southeast 
Seventh St., Boca Raton. FL 
33432, (305) 392-6597. 

• BBS IN FOX RIVER 

FORMS CLUB-Simplified 
Computer Solutions in 
Wisconsin has helped to 
form the Green Bay/Fox 
River Valley's bulletin-board 
service, SCS ABBS. The SCS 
Users Group evolved from 
the BBS and provides 
members with access to a 
library, group purchasing, 

[continued] 



58 BYTE- APRIL 1985 



PERSONALITY 
PROBLEM? 

UNIX™ and DOS™ At the Same Time! 




Also 
available 
on the 
PC/XT and 
compatibles 






Looking at an IBM PC/AT? Happy with DOS but want 
UNIX? Happy with UNIX but want DOS? Want them 
working together? 

Get The Connector!™ 

The Connector is a revolutionary product that allows 
DOS applications to run on the IBM PC/AT or XT 
under VENIX/86 ( the first licensed AT&T UNIX 
operating system for the IBM PCs) or PC/IX. That 
means you can add one or more terminals to your AT 
which run programs using multi-user VENIX/86 to 
share the disk and printer. Switch between UNIX and 
DOS at the console with a single command. And run 
more than one task simultaneously. Like running a 
spelling check in the background while you print a 
report and run Lotus 1-2-3™ or dBaselF? 

Get yourself an AT and load it with VENIX. Collect 
your DOS and/or UNIX applications. We'll supply The 
Connector. The right solution to your software per- 
sonality problems. 

Call for complete details. 

Unisource Software Corp., Department 4109, 
71 Bent Street, Cambridge, MA 02141 . 
Telex 92-1401/COMPUMART CAM. 

617-491-1264 






UNIX ii. a trademark of AT&T Technologies. Inc IX >S »-. a trademark of Mta as oft, In*. PC' AT and PC/XT are trademarks of IBM, The Connector is a trademark 
of Uniform Software Systems Inc VENIX/86 implementation by VcnturCom, Inc. 1-2-3 and LOTUS are trademarks of Lotus Development Corp dBasell is a 
trademark of AshtonTate. 

Inquiry 392 



Getting UNIX Software 
Down to Business 

APRIL 1985 -BYTE 59 



Q 



COMPUTERBANC 



GET SERIOUS. STOP PAYING HIGH PRICES NOW! 

THOUSANDS OF AVAILABLE ITEMS. CALL FOR COMPLETE PRICING. 



SYSTEMS 
IBM PC 

256K, Two 360KB Disk Drives, Color 
Graphics/Monochrome Graphics board, 
Parallel Printer Port, Monochrome Display 
(Amber/Green), DOS 2.1. 
LIST PRICE $2950.00 - ONLY $2095.00 

SUPER XT 10 Meg Upgrade $2795.00 

IBM AT 11 % OFF 

IBM SOFTWARE 

LOTUS 1-2-3 $289.00 

LOTUS Symphony 425.00 

MICROPRO Wordstar 249.00 

ASCII Express For IBM 125.00 

Wordstar Professional 359.00 

Infostar 249.00 

Multimate 269.00 

MICROSOFT Word 229.00 

Word W/Mouse 279.00 

Multiplan 139.00 

Project 159.00 

ASHTON TATE Friday 179.00 

dBASEII 280.00 

dBASE III 349.00 

Framework 359.00 

LIFETREE SOFTWARE Volkswriter . 119.00 

Volkswriter Deluxe 169.00 

FOX & GELLER Quickcode 139.00 

dUtil 59.00 

dGraph 149.00 

MICRORIM Rbase 4000 295.00 

PFS Write 89.00 

File 89.00 

Report 89.00 

Proof 79.00 

Access 79.00 

ENERGRAPHICS 269.00 

IBM HARDWARE 

AST Six Pack Plus 64K 259.00 

MegaPlus II 259.00 

PC Net 1 Starter Kit 830.00 

QUADRAM Quadboard O-K 219.00 

Quadcolor 1 or Microfazer 64K 205.00 

Quadlink 479.00 

MICROSCIENCE 

10MB Winchester 679.00 

FRANKLIN TELECOM 

10 Meg Harddisk 719.00 

22 Meg Harddisk CALL 

Cartridge backup CALL 

HERCULES Mono Graphics 329.00 

Color Card 199.00 

ORCHID Turbo CALL 

PC Net Starter Kit CALL 

PLANTRONICS Colorplus 389.00 

STB Rio plus 64K 249.00 

Super Rio 259.00 

Graphix +II NEW 309.00 

AT Hardware CALL 

TEAC55B 124.00 

55F 180.00 

TANDONTM 100-2 179.00 

IBM Floppy 1.2 Meg CALL 

TALL GRASS 12MB W/Tape 2395.00 

RAM 64K upgrade set 9 35.00 

MOUSE SYSTEMS Optical Mouse. . . . 189.00 
ALSO - XCOMP, PERSYST, ORCHID, 
TITAN AND OTHERS 

PRINTERS 
BROTHER HR-15 369.00 

HR-25 619.00 

HR-35 859.00 

2024LQ 915.00 

JUKI 6100 429.00 



NEC 2030 659.00 

2050 799.00 

3530 1229.00 

3550 1539.00 

STAR MICRONICS Gemini 10X 259.00 

Gemini 15X 389.00 

EPSON RX-80 F/T 329.00 

FX-80 349.00 

FX-100 649.00 

LQ1500 .1299.00 

OKIDATA 92A 389.00 

93A 649.00 

84A 949.00 

PANASONIC 1091 CALL 

TOSHIBA 1350-P 1399.00 

MONITORS 

AMDEX300 129.00 

300A 145.00 

310A 169.00 

Color l+ 269.00 

Color II 459,00 

TAXAN Composite Amber 119.00 

121/122 149.00 

420 (RGB).. 439.00 

415 (RGB) 489.00 

PRINCETON GRAPHICS HX-12 469.00 

SR-12 625.00 

MAX-12 189.00 

ZENITH ZVM-122 Amber 95.00 

ZVM-123 Green 95.00 

NEC 1201 Hi Res Green 115.00 

1205 Hi Res Amber 115.00 

1206 Green 79.00 

JC1215 Composite Color w/audio . . . 215.00 
JC1216 Color RGB 329.00 

MODEMS 

HAYES 1200 469.00 

1200B 389.00 

300 199.00 

Micromodem //e 219.00 

ANCHOR Mark X 109.00 

Mark XII 249.00 

Volksmodem 59.00 

NOVATION Smart Cat Plus CALL 

Access 1-2-3 419.00 

Apple Cat II 239.00 

J-Cat 99.00 

PROMETHEUS Promodem 1200 329.00 

APPLE PRODUCTS 

MICRO SCI A2 drives 179.00 

RANA ELITE 1 219.00 

TEAC drive 189.00 

APPLE Compatible drive 169.00 

WESPER interface 69.00 

BUFFERED 16K 139.00 

SYSTEMS SAVER Fan 69.00 

MICROSOFT Premium //e 279.00 

Softcard CP/M 229.00 

Multiplan... 129.00 

MAC Multiple (Macintosh) 129,00 

Basic (Macintosh) 109.00 

APRICORN Serial Card 69.00 

Z-80 Card 59.00 

ASCII Express Professional 89.00 

DISKETTES S/S 12.00 

D/S 19,00 

KOALA Touch Tablet... 79.00 

HAYES Mach III Joystick 39.00 

THUNDERCLOCK 119.00 

APPLEMOUSEII 129.00 

VIDEX Ultraterm .....179.00 

80 C0LUMN/64K lnterface//e only . . . 99.00 
80 COLUMN Card II + only 59.00 

WE SUPPORT THESE FINE SYSTEMS: 
Apple, Compaq, IBM, and many mora. 



TELEX #550757 /ANSWER BACK - COMPUTERBNK UD 



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Orders Only 
800/332-BANC 



OUTSIDE CALIFORNIA 



COMPUTERBANC 



16783 Beach Blvd., Huntington Beach, CA 92647 

714/841-6160 inquiry 89 





jxrod. MHM m*cruJKf«M 
ll|«1 10 I 10*4 Mlw.ino •« 
Lttm ti 00 minimum, i or 




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CLUBS & NEWSLETTERS 



conferencing on the BBS, 
and a monthly newsletter. 
The annua! dues are $10. 
Contact Don Sanderfoot, 
SCS, 2175 Wildwood Dr., 
Little Suamico, WI 54141. 

• BUSINESS BBS 

The Tulane University 
Business Bulletin Board 
(TUBBB) system combines 
business researchers, faculty, 
alumni, and students on line 
to share ideas, data, and 
programs. Contact lohn 
Page, A. B. Freeman School 
of Business, Tulane Univer- 
sity, New Orleans, LA 70118. 

• JOIN LONE STAR 

The Lone Star Computer 
Club of Racine, Wisconsin, a 
group of users of all kinds 
of computers, meets at 7:30 
p.m. on the second Thurs- 
day of each month at the 
Douglas Avenue Park Com- 
munity House. The monthly 
newsletter, President's Newslet- 
ter, combines articles, soft- 
ware reviews, regular 
features, and library and 
system notes with applica- 
tions. Contact H. S, Kanecki, 
Lone Star Computer Club, 
POB 93, Kenosha, WI 53140. 

• VICTOR 9000 IN NW 

The Victor 9000 Users 
Group serves users in 
Oregon and southern 
Washington state by meeting 
regularly to discuss the 
merits of the Victor 9000 
business computer. A 
monthly newsletter, discount 
purchases, software demon- 
strations, and support for 
new users are group 
benefits. Contact Alan 
Bergen, 11765 Southwest 
Ebberts Court, Beaverton, 
OR 97005. 

• KAYPRO IN BALTO 

The Kaypro Users of 
Baltimore (KUB) meet at 
7:30 p.m. on the first and 
third Wednesdays of every 
month at Loch Raven Middle 
School in Baltimore, 
Maryland. The Bear Facts 
Newsletter contains further in- 



formation. The annual fee is 
$12 and requires a blank 
disk as an initial contribu- 
tion. Newsletter subscrip- 
tions are an additional $6. 
Write KUB, POB 23510, 
Baltimore, MD 21203. 

• ZORBA IN U.S. 

The Zorba Equipment Users 
Society (ZEUS), a source of 
information and support for 
Zorba owners nationwide, 
maintains a public-domain 
library. The newsletter, Oracle 
of Zeus, is produced six 
times a year on disk and 
contains up to 30 files of 
relevant information. The 
$2 5 annual membership fee 
covers a subscription to the 
newsletter, Contact Randy 
Brook, ZEUS, POB 1112, 
Athens, OH 45701. 

• EXPLORING THE STARS 

Users of MicroPro's Word- 
Star and InfoStar can sub- 
scribe to two Stargazer 
newsletters, Exploring WordStar 
and Exploring InfoStar. 
Designed to unlock the 
potential of the programs, 
they supply information for 
solving application questions 
and clarifying documenta- 
tion through a practical, 
hands-on approach. 
Members are encouraged to 
submit articles and can 
benefit from group-purchase 
discounts. Subscriptions are 
$24 annually per newsletter 
or $40 for both. Contact 
HI-Tech, Department B, 4 
Harwood Dr., Glen Cove, NY 
11542. 

• MAC GETS TECHNICAL 

A Macintosh Programming 
journal, MacTech, reviews soft- 
ware development and pro- 
gramming exclusively for the 
Mac Each month articles 
written by a panel will build 
on previous columns, en- 
hancing readers' understand- 
ing of how to best apply 
Macintosh software tech- 
nology. The subscription 
rate is $24 a year. Contact 
MacTech, POB 846, Placentia, 
CA 92670, (714) 993-9939. ■ 



THE SIMPLE APPROACH 
IS THE SYMBOL APPROACH 



10S=0 1 


V REAL X( 100) 1 


i 


20F0RI=1 TO 100 1 


i READ* N.ttCDJ- 1 ,N) 1 


[ 


30 INPUT X 1 


5=0 




40 IF X = GOTO 70 1 


DO 1 1= 1 ,N 


(«7X)*pX«-0 


50 S=S+X 1 


I 10 S-S+XCD 




60 NEXT I j 


1 PRINT * S/N I 


I 


70 PRINT 5/(1-1) 1 


1 END 1 


L 


BASIC 

program to calculate averages. . . 


FORTRAN 

just shrunk from seven lines. . . 


POCKET APL 

to one. 



INTRODUCING POCKET AFC! 

Pocket APL, a new PLUS* WARE™ product, 
symbolizes a whole new way to solve problems. 
Faster than Fortran. Simpler than Basic. And at a 
cost much less than Cobol and many other pro- 
gramming languages. Its use of symbols makes it 
concise and efficient— powerful and productive. 

WORKING IN SHORTHAND = 
WORKING FASTER, SMARTER. 

Pocket APL allows you to shrink 
the length of your programs. Because 
just a few symbols say what takes lines 
and lines to say in other programming 
languages. So Pocket APL cuts the 
drudgery and need for tedious sub- 
routines and long lists of commands. 

GET FLEXIBILITY > 
WITH CANNED SOFTWARE. 

Pocket APL is a complete APL 
implementation with enhancements 
like online HELP, windowing, report 
formatting, dual file system, and 
debugging aids. It's also a powerful 
online calculator. So you don't have 



BBSS 54 * 




to switch back and forth between programs or from 
your hand-held calculator to the computer. 

And the symbols? Simple. You'll learn them fast. 
They'll become as second nature to you as + , - , 
x , and ■«-. Once you start using them, you'll be 
programming four to 10 times faster than with 
conventional languages. And as your needs grow, 
you can easily upgrade to STSC's APL*PLUS®/PC 
System for even more features— like 
communications and graphics. 

POCKET APL COSTS 
MUCH < YOU'D EXPECT. 

Pocket APL makes programming 
easy. And priced at just $95, it's easy 
on the budget, too. It works with IBM 
PC's and compatibles and requires 
only 128K. So if problem-solving is 
taking up too much of your time, the 
answer is symbol. Pocket APL. 

To order, or for more information, 
call 800-592-0050. In Maryland, call 
(301) 984-5123. 

Or write STSC, Inc., 2115 East 
Jefferson St., Rockville, MD 20852. 
All major credit cards accepted. 



Problem-solving at the speed of thought. 



^V^JI Pocket APL uses a soft character set for computers with IBM-compatible graphics board or color monitor; keywords for computers with monochrome. Optional 
^P | ^P^M charactGr generating ROM can be ordered for IBM PC monochromes or Hercules monochrome boards 

AContei Company PLUS* WARE and Pocket APL are trademarks of STSC, Inc. APL* PLUS is a service mark and trademark of STSC, Inc., registered in the U.S. Patent and Trademark 
Office and in other countries. 

Inquiry 416 APRIL 1985 • B Y T E 61 



THE MAINFRAME 



When one of twenty Micro Mart 
Sales Pros answers a call, he's ready 
at his PC. 



Micro Mart's Ten Million Dollar 
Inventory is on-line with our IBM 
Mainframe, so answers are fast 
and accurate. 



With PC to Mainframe Inven- 
tory, this Micro Mart Salesman 
verifies his stock, quotes his best 
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APRIL 1985 -BYTE 63 



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BOOK REVIEWS 



BUILD YOUR OWN 
EXPERT SYSTEM 
Chris Naylor 
John Wiley & Sons 
New York: 1985 
246 pages, $13.95 

ARTIFICIAL 

INTELLIGENCE IN BASIC 
Mike James 
Focal Press 

Stoneham, MA: 1984 
122 pages, $14.95 

THE COGNITIVE 
COMPUTER; ON 
LANGUAGE, LEARNING, 
AND ARTIFICIAL 
INTELLIGENCE 
Roger C Schank 
with Peter G. Childers 
Addison-Wesley 
Reading, MA: 1984 
282 pages, $17.95 



BUILD YOUR OWN 
EXPERT SYSTEM 
Reviewed by 
Ramachandran 
Bharath 




An increasing number of comprehensive introductions 
to expert systems— computer programs that emulate 
the decision making of human experts— have been pub- 
lished recently. Tro examples are Building Expert Systems by 
Frederick Hayes-Roth (Reading, MA: Addison-Wesley, 
1983), and A Practical Guide to Designing Expert Systems by 
Sholom M. Weiss and Casimir A. Kulikowski (Totowa, NJ: 
Rowman and Allanheld, 1984). 

But the object of Chris Naylor's book, Build Your Own Ex- 
pert System (originally published in the United Kingdom in 
1983), is to help home computer users write expert sys- 
tems that learn. 

John F Sowa, author of Conceptual Structures: Information 
Processing in Mind and Machine (Reading, MA: Addison-Wesley 
1983), groups expert systems into three categories based 
on the kinds of problems they address: classification (such 



as diagnosis of disease), de- 
sign (of chips, for example), 
and decision support. 
Naylor's book is aimed 
essentially at teaching 
readers about classification 
problems. 

Naylor begins with a 
good discussion of the 
general advantages and 
limitations of current expert 
systems. He follows this 
with a chapter on statistical 
and probability theories; he 
provides the essentials of 
elementary probability 
theory and discusses revis- 
ing initial estimates of prob- 
abilities in light of relevant 
additional information. (The 
technique for such revision 
of initial estimates is known 
as Bayes' theorem.) Naylor 
introduces these concepts 
extremely well by relating 
them to an expert system 
the reader might want to 
build: a program for fore- 
casting weather using infor- 
mation on current condi- 
tions of fog, humidity, tem- 
perature, etc. 

After providing this background, the author leads the 
reader through the process of developing a general BASIC 
program that can solve a broad range of classification 
problems. The process includes a BASIC program that asks 
the user questions regarding the variables relevant to the 
problem and the outcomes possible in the problem. The 
program then must be given examples of the different out- 
comes and of the values of the associated variables. The 
program can handle any problem that has these charac- 
teristics; a set of variables relevant to the problem; dif- 
ferent outcomes distinguished by a different pattern of 
values for the variables; and the pattern of values of the 
variables indicates which outcome would result. 

A concrete example of this abstract definition is medical 
diagnosis. Here, the pattern (symptoms) tells the doctor 

[continued) 



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APRIL 1985 'BYTE 65 



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BOOK REVIEWS 



which outcome (disease) is indicated. The pattern is rep- 
resented by a set of variables: a 1 in a particular variable 
means the symptom that variable represents is present; 
a stored means it is not. Another example is a fault- 
diagnosis problem to test Naylor's expert program. In this 
problem, the possible variables are the faults you might 
observe in a cassette recorder: no lights; tape won't move; 
unit won't record; intermittent sound; distorted sound; er- 
ratic speed; and hum. Depending on which subset of these 
seven variables is operative, you can determine which out- 
come (or fault) you should diagnose, such as the switch 
is off, the tape jammed, the tape was inserted wrongly, 
the head is dirty, or there's a problem with the amplifier. 
(An optional extension of this is incorporated in a listing.) 
Using the diagnosis as the input, the extension offers as 
output a suggested remedial action— clean the head, 
switch on the recorder, etc— that is, it is a two-node (or 
two-stage) classification problem. 

The second stage classifies the faults to produce 
remedial action. Readers can come up with their own ex- 
amples of situations that fit this general classification-prob- 
lem format. By finding a suitable problem that relates dif- 
ferent subsets of a set of variables to different outcomes, 
the general program can be used for diagnosis. 

In the course of developing this general program, Naylor 
introduces the theoretical concepts underlying the general 
classification problem, referred to in texts on statistical 
theory as multiple discriminant analysis (the problem of 
discriminating or distinguishing between different out- 
comes on the basis of information regarding the dis- 
criminating variables). By the time readers work through 
the explanations of each line of the program and what 
it does, they will have learned useful statistical theory 
related to a problem that holds their interest. 

The author explains the fundamental basis of all diag- 
nostic or classification-type expert systems. He illustrates 
how they are essentially a set of IF (set of symptoms) 
THEN (corresponding outcome or diagnosis) statements. 
These are usually referred to as "production rules." He 
discusses major successful expert systems, like MYCIN, 
for medical diagnosis; Prospector, for geological prospect- 
ing; and DENDRAL, for chemical analysis. The book is 
worth reading just for this lucid explanation of the basis 
of current systems and for the discussion of making a pro- 
gram so specific to a particular problem area that it can- 
not be easily adapted to a different problem area. In con- 
trast, the programs Naylor teaches readers to build are 
of the learning type; that is, on the basis of examples of 
different types of problems, they can learn to diagnose 
problems in different areas. He points out that the disad- 
vantage of this is that such a general program would not 
be as efficient as one built for a specific purpose. 

Summary 

I highly recommend this book for several reasons. It pro- 
vides a simple yet insightful discussion of extant successful 

[continued] 



66 BYTE' APRIL 1985 



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BOOK REVIEWS 



expert systems. It teaches the basic principles of statistical 
theory, production rules, learning algorithms, and so forth 
in a practical way and provides a technical summary at 
the end of the book for reference. The book contains a 
program for an expert system that is based on an applica- 
tion of Bayes' theorem. 

Running the program in chapter 7 helped immensely in 
following Naylor's explanations. Also, verifying that the 
sample program produced the results indicated by the 
author confirmed that 1 was on the right track. The pro- 
grams are given in Apple 11 and Spectrum versions of 
BASIC. The reader with access to a different system (I had 
to modify the learning program for the IBM Personal Com- 
puter) becomes painfully aware of the difficulty of under- 
standing the logic of another person's BASIC program 
when it is written in a version that uses only single-letter 
names for variables. Naylor mentions the unsuitability of 
BASIC for these types of programs; his choice was based 
on the fact that it is the language most commonly available 
for home computers. Now that microcomputer versions 
of a more suitable language, Prolog, are becoming avail- 
able, I hope Naylor's next edition of the book will pro- 
vide micro-PROLOG listings as well. 

Ramachandran Bkarath is a professor in the Department of Manage- 
ment, Marketing, and Data Processing at Northern Michigan Univer- 
sity [Marquette. Ml 49855|. 



ARTIFICIAL INTELLIGENCE IN BASIC 
Reviewed by Norman I. Chaplin 

The artificial intelligence (AI) invasion that was once 
predicted has now arrived. In fact, this intelligence has 
established itself in the areas of intelligent games, deci- 
sion analysis, and expert systems, in addition to programs 
that correct spelling and grammar. 

Mike lames, the author of Artificial Intelligence in BASIC, 
believes the best way to comprehend the scope of Al is 
to gain experience in it. He recommends using BASIC, 
which is both widely understood and easily read. 

To illustrate different techniques, lames uses a few sim- 
ple problems that are repeated in various branches of AI. 
He provides practical programs that can be entered with- 
out prohibitive effort from a keyboard. His BASIC dialect 
is a standard Microsoft version without special features; 
it can be adapted readily to most home computers. 

lames uses a heuristic attack on the familiar nine-square 
problem (arrange 8 numbered tiles in numerical order 
within a 3 by 3 array). He defines a heuristic rule as one 
that, when applied, tends to make the result move closer 
to the solution. With a heuristic, as opposed to an 
algorithm, there is no guarantee that a solution will be 
found, The path of the heuristic may be diverted into a 
closed loop of repeating positions. The program prints 
the board position to the screen every two to four moves 
and prints out the total number of moves taken to reach 



68 B Y 



APRIL 1985 



Inquiry 67 



BOOK REVIEWS 



a solution. Although many of my attempts ended in con- 
tinual cycling through a particular sequence of moves, ! 
generally solved the problem in twenty to sixty moves, 
and sometimes in as few as seven or eight. 

Man and Machine 

The opening chapter discusses 'Tour Computer's IG," 
"Computer-Aided Intelligence," and "What Is Intelligence?" 
In the sections on pattern recognition and speech pro- 
duction and recognition, lames admits that these subjects 
are too much for BASIC and are best handled with dedi- 
cated hardware. A discussion of grammar leads to an ex- 
ample of English generated by a computer. 'Thinking, Rea- 
soning, and Problem Solving" deals with mathematical 
theorem proving, cybernetics, and human associative 
memory. 

Man teaches machine in chapters 4, 5, and 6. Man in- 
structs the program Aardvark to recognize animals. To ac- 
complish this, Aardvark asks a series of questions to build 
up its inventory of identifiable animals until it becomes 
an expert in animal identification. Aardvark is rudimen- 
tary, but with some expansion it could become a prac- 
tical program, useful in fields such as mineral identifica- 
tion. I used it for bird identification. 

"Structure of Memory" discusses the problem of mem- 
ory-recall and explains computer solutions such as rela- 
tional stores and conceptual databases, lames fully il- 
lustrates the conceptual database problem with the Tom 
the Cat program, which solves the recall problem using 
a number of corresponding matrices. If you enter TOM 
IS A CAT CAT HAS FUR: and then inquire, Does Tom have 
fur? the program answers YES. (Tom wouldn't run until 
1 eliminated its bugs.) 

Language and Philosophy 

Another chapter deals with language: syntax, parsing, and 
semantics. Several pages cover Eliza, the psychotherapy 
program. There is also a listing and description of a BASIC 
program, Chat, that generates English sentences. 

The last chapter is about philosophy. Can a computer 
program be intelligent? Or merely very clever? What about 
awareness? Should the Turing test be modified to measure 
artificial intelligence? The theme of this book could be 
summarized in James's words: "There is nothing very dif- 
ferent about intelligent programs and they can be under- 
stood without any difficult theory." Neurophysiology shows 
us how small groups of neurons work, functions that we 
can duplicate electronically. Psychology, however, is so 
genera] that it can provide little practical guidance. James 
emphasizes that the third-generation software beginning 
to appear is characterized by the assumption that any mis- 
understandings are the program's fault, and the program 
will attempt to correct its mistake by learning the mean- 
ing of the new input from the user. This could be inter- 
preted as intelligent behavior. I loaded a Commodore 64 
with the Chat program, made a few changes, and found 

{continued} 



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BOOK REVIEWS 



the answers from such a short program to be thought-pro- 
voking. The program generates ideas, which is a form of 
creativity. But is it creativity from the machine that ar- 
ranges the word symbols, or from the man who interprets 
those symbols 9 Or both 9 Is this machine-aided creation? 
The sentences generated by Chat are enigmatic, but that 
could be changed by programming some restrictions on 
word association. The meaningless sentences would be 
reduced by this and further suppressed by a supervisory 
censor. We could even program it to learn from human 
prose. But would we then be restricting creativity? 

If you are already competent in AI, Artificial \ntelligence 
in BASIC is not for you unless you would like to instruct 
others. It could be a useful text for a short laboratory 
course in which the existing programs could be extended 
as exercises, or it could serve as a practical supplement 
to more theoretical material. It is superb as an introductory 
text for study at home. The programs are short enough 
that you could enter most in less than half an hour. 

The knowledge attained from these short BASIC pro- 
grams is readily transportable to other, more efficient 
languages, where it can become a tool for construction 
of large, more practical Al programs. 

Norman I, Chaplin (3155 South Dr., Mlentown, PA 18103) is a 

retired designer in VLSI now actina as a writer and consultant. 



THE COGNITIVE COMPUTER 
Reviewed by Darrow Kirkpatrick 



Roger Schank, director of Yale University's Artificial In- 
telligence Project, has succeeded in writing a clear, 
exciting report on the nature of human intelligence and 
the implications of machine intelligence. Explaining his 
research, Schank tells us how much we must know about 
computers, what we can learn about intelligence from the 
development of understanding computers, and how intel- 
ligent computers will affect our world. 

Setting the Record Straight 

Schank risks distilling his 20 years of research into one 
nontechnical book about artificial intelligence. This is his 
attempt to set the record straight. Along the way we can 
learn a little about how computers work and a great deal 
about how human beings think, learn, and understand. 
Schank thinks learning about AI research is more impor- 
tant for an understanding of computers than learning to 
program in BASIC (or any of the other computer-literacy 
skills in vogue). Al research has the potential to transform 
our lives through the creation of new machines that can 
do things never done before. 

Cognitive Understanding 

If we want to build understanding computers, first we must 
understand ourselves; we must be familiar with human 

{continued) 



70 



BYTE • APRIL I985 



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BOOK REVIEWS 



thought processes before we can program an understand- 
ing computer. Schank defines three levels of understand- 
ing: making sense, cognitive understanding, and complete 
empathy. Current AI research is concerned mostly with 
cognitive understanding. Cognitive computers will be able 
to learn, relate the present to the past, formulate new in- 
formation, and explain themselves. 

People understand in terms of their own experiences. 
We can understand only if our memories are able to 
change to match a situation. In a sense, we are pro- 
grammed by our experiences. But intelligent entities can, 
at best, "make sense" of experiences they haven't had. 
Computers will never understand us at the level of com- 
plete empathy because they are not like us. 

Intelligence is the ability to react to something new in 
a nonprogrammed way. The fundamental difference be- 
tween imitation and understanding in a system is self- 
knowledge. An intelligent system must be able to explain 
itself. 

Because AI research is a new and different science, every 
major AI project is in some sense a failure at modeling 
human intelligence. Each success shows only what is miss- 
ing. AI is a steady but plodding study of the impossible. 
As it asks questions about language, reading, and under- 
standing, it can lead us to appreciate human qualities and 
abilities even more. 

AI research has an uneasy relationship with computer 
science. Computer scientists are searching for ways to 
make computer hardware and software work more effi- 
ciently, but AI researchers are attempting to raise the level 
of understanding of computers. Ultimately, Schank feels, 
AI will be assimilated into other disciplines. 

Schank defines product-directed AI as concerning the 
technology of getting computers to do intelligent things, 
and theory-directed AI as concerning the representation 
of knowledge, learning, and human thought processes. Ex- 
pert systems are examples of product-directed AI. 

Language and Knowledge Structures 

Until recently, the representation of abstract ideas and 
concrete events has been possible only with natural lan- 
guages. Computers also must be able to handle abstract 
concepts, but a system will not seem very intelligent with- 
out also having a clear grasp of the obvious. In a 
humorous progression of examples of conceptual errors 
in the development of an early AI program. Schank dem- 
onstrates just how obscure the obvious can be. 

Our memories are tuned to ideas, not words. A major 
task in AI programs is making the computer forget the 
words and retain their meanings. An understanding system 
must rely on very basic conceptual representations of 
events. The Yale Artificial Intelligence Project utilizes 
only 1 1 primitive actions to represent real-world 
happenings. 

An interesting thing about human knowledge is not how 
much we know, it's how effortlessly we recall what we 
know. One of the basic methods used to represent knowl- 



edge in AI programs is the "script." Scripts enable com- 
puters to deal with everyday, stereotypical situations by 
using a group of connected possibilities, or "slots," and 
rules for filling these slots. 

But if computers are to understand more than stereo- 
typical situations, they must have some knowledge of why 
and how people do what they do. Computers must have 
knowledge structures for goals and plans. 

Early AI research concentrated on the outer form of lan- 
guage by building parsers to dissect language into its 
grammatical elements. Current research is occupied with 
understanding the content of communication. For Schank 
and others, language is a vehicle rather than an end; the 
aim is to write programs that concentrate on meaning 
rather than on grammatical structure. 

In the early 1970s Schank and his students built soft- 
ware programs called the Inferencer and the Paraphraser. 
In order to process sentences and make conclusions, the 
Inferencer could parse draw inferences, and generate nat- 
ural language. The Paraphraser could understand a sen- 
tence well enough to restate it in different ways, from dif- 
ferent perspectives. However, to understand large pieces 
of text, computers must draw inferences from many con- 
nected sentences. 

A computer can use scripts to make up for the lack of 
logical connections between events, but researchers have 
to give the computer methods for dealing with the world 
when it does not have a script. More sophisticated AI pro- 
grams use beliefs, inferences, plans, goals, scripts, and 
prior memories in order to understand. Researchers have 
seen the importance of a dynamic, flexible memory that 
changes every time it understands something. 

In the long term, it is unrealistic for us to expect to build 
perfectly general knowledge structures into computers. In- 
stead we must give them the ability to learn. This is the 
only way computers will be able to make connections 
across different fields of knowledge— thereby solving what 
Schank calls the "domain problem." Computers will have 
to know what they don't know as well as what they do 
know. 

AI in Education 

I suspect that first among Roger Schank's priorities is 
teaching. He has strong opinions about education. The 
issue is not how much we must learn about computers but 
what we can learn from them. 

Schank thinks children should first learn to read and 
write. Public schools and teachers are not equipped to 
train children for programming careers. Schank concludes 
that children are better off with no programming skills 
rather than poorly taught computer skills. 

Schank thinks that children must learn at an active, in- 
dividualized pace. Children must actually learn, not just 
repeat, new principles. Experimentation with computers 
can provide this kind of learning. 

For Schank, education is the most important and poten- 

[cont'mued) 



74 BYTE- APRIL 198^ 



Where Giants Fear To Tread 




For five years NESTAR has ventured where giants have feared to 
tread-local area networking. In fact NESTAR has installed more 
large local area networks in large institutions than any other 
manufacturer 

Soon the giants will be involved in networking and that will 
ensure broad industry support. NESTAR's products will be totally 
compatible and complementary to the systems 
sold by the giants. That way you receive the 
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Call or write for your copy of: 
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Inquiry 282 



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745158 16 
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74C165 16 1 29 
74C173 16 89 
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74C175 16 1.19 
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74C193 16 1 39 
74C195 16 129 
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74C903 14 
74C906 14 
74C907 14 
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LF356N S 109 
LM358N 1 59 
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LM373N 14 4 95 
LM3/7N 14 1 95 
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LM3B4N! 14 195 
LM1RON il a 89 
LM387N B 1 39 
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LMaStN-aOM 1.19 
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LM393N B 45 
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LM399M 595 
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NE544N 14 1 95 
NE550A 14 1 95 
NE555V 8 35 
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LM556N 14 .79 
NE558N IE 159 
ME564N 16 1 95 
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NE571N 16 2.49 
NE592N 14 1 19 
LM703CN B 1 49 
LM710N 14 69 
LM711N 14 79 
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LM733N 14 89 
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LM748N 1 
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LM1800N 16 
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LM1889N 18 
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C04042 16 
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C04044 16 

16 89 
CD4047 14 89 
CD4048 16 59 
CD4049 16 39 
CD4050 16 39 
C04051 16 
(,114052 16 89 
CO4053 16 79 
CD4056 16 

24 1.95 
C04060 16 89 
CJOtWb 14 45 
CD4068 14 39 
CO4069 14 35 
CD407O 14 29 
CO4071 14 29 
OM072 14 29 
CO4073 14 ?9 
CO4077 14 .15 
C04078 14 4 ■ 
CD4081 14 29 
CD4093 14 49 
CD4QS4 IE 195 
C0409B IE 1 95 
CD4099 IE 1 89 


CD4503 

CO4508 
CO4510 
CW5I1 
C04512 
C045I4 
C04515 
C04516 
C04516 
CD4519 
CD4520 
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CD4528 
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MR* 

6 am LP 

14 pin LP 
lb pin LP 

15 (wi LP 

20 pm I P 

2? pm LP 
24 .mi LI 
28 pin LP 


■ ...... JkUUmWUt 

m m 

SoiderUi) (Gold) Standart 
)e (Tin( Sockets ,*,„ , 9 IM9 m . n 


Wire Unp ^j 
Sockets ^ m 
(Gold) Lew) =3 

Pin Ha 1-9 16-99 100* 


Header Plu§s (Gold) 


fp.nWvV 55 49 45 
Uip-nWW 69 65 59 

■ i . - mm 75 69 

16 pin WW 79 72 65 
'- .in- WW 95 65 75 
!0pmWW1.19 1.09 95 

,',' ..III WW 1 2:1 1 1-1 111', 

24 inn WW 1 35 1 19 1 08 
28 pin WW 169 1.55 i 19 
id urn WW1 89 t.79 IBS 
40pinWW229 195 179 


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II 14 I"' | I4p 

17 i- 14 | 16 pm 

19 17 16 IHjJWSG 65 59 51 

26 24 23 2D pm SG 75 85 59 

30 27 2b 22 pm SG 79 6 
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PwlHo 1 9 IU99 ll»«i 




; HI 65 59 55 

24 pm HP i 15 .99 89 


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S10 Minimum Order - US Funds Only CA Residents Add 6^% Sales Tax Spec Sheets - 30e each 

Shipping Add 5 " - plus S1 50 Insurance Send $1 Postage fof FREE 1985 Jameco Catalog Prices Subject to Change 

Send stamped, seif-addnsssed envelope to receive a Monthly Sales Flyer - FREE' 




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sterCard 






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- Telex: 1 76043 




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HONE ORDERS 


WELCOME - 


- (415) 592-8 


30003 


1 982 Nat. Linear Data Book 1 1957 pgs i . $1 1 .95y 


/ 



76 B V T E 



APRIL !W 



Commodore Accessories ProModem 1200 and Options Apple" Accessories 



RS232 ADAPTER FOR 
VIC-20 AND COMMODORE 64 




*"*, 



c e 



The JE232CM allows connection of standard serial RS232 
printers, modems, etc. to your VIC-20 and C-64. A 4-pole 
switch allows the inversion of the 4 control lines. Com- 
plete installation and operation instructions included. 

■ Plugs into User Port • Provides Standard RS232 signal 
levels • Uses 6 signals (Transmit, Receive. Clear to Send. 
Request to Send. Data Terminal Ready. Data Set Ready). 

JE232CM $39.95 



VOICE SYNTHESIZER 
FOR APPLE AND COMMODORE 



JE520CM 




JE520AP 



• Over 250 word vocabulary -affixes allow the formation of more 
than 500 words • Built-in amplifier, speaker, volume control, and 
audio jack ■ Recreates a clear, natural male voice • Plug-in user 
ready with documentation and sample software • Case size: 
7'A"L x 3VTW x 1-3/8"H 



APPLICATIONS: 

Part No, C 

JE52QCM 

JE520AP 



• Security Warning 

• Teaching 

• Instrumentation 



• Telecommunication 

• Handicap Aid 

• Games 



For Commodore 64 & VIC-20 $114.95 

For Apple II. ll+anrU/e $149.95 



Computer Memory 
Expansion Kits 



IBM PC, PC XT and Compatibles 

Most of the popular Memory Boards leg Quadram " Expansion Boards) 
allow you to add an additional 64K. 128K. 192Kor256K The IBM64K Kit will 

; j ";'Ui-iti- 1 ■ begird . m 64K byte iments IT* Kll i i simple to Install 

lust insert the 9 ■ 64K RAM chips in the provided sockets and set Ihe 2 groups 
of switches Complete conversion documentation included 



IBM64K (Nine 200ns 64K RAMs) $33.49 

IBM PC AT 

Each kit comes complvlc with nine ' ?8K dynamic RAMs and dot' umenlation 
tor cohesion 

IBM128K (Nine 250ns 128K RAMs) $199.95 

APPLE He 



JE864 $99.95 

TRS-80 MODEL I, III 

Each Kit comes complete with eight MM529G (UPD4 1 6/4 11 6> 1 6K Dynamic 
RAMs and documentation for conversion Model I 16K equipped with Ex- 
pansion Interfaci' ran >.» . ,| u oil I.. l,-,h with .' Kits Model III ( ,in he 
expanded from I6K lo 48K using 2 Kits Each Kit will expand computer by 
16K increments 

TRS-16K3 200ns (Model III) $6.29 

TRS-16K4 250ns (Model 1) $5.49 

TRS-80 MODEL IV & 4P 

Easy to install Kit comes complete with 8 ea 4 1 64N-20 (200ns) 64K Dynamic 
RAMs and conversion documentation Converts TRS-80 Model IV computers 
Irom 16K lo 64K Also expands Model 4P trom 64K to 128K 

TRS-64K-2 $29.95 

[Converts the Model IV from 1 6K to 64K or will expand the Model 4P from 
64Kto 128K) 

TRS-64K2PAL (Model IV only) $49.95 

(8 - 4164s with PAL Chip to expand from 64K to 128K) 

TRS-80 COLOR AND COLOR II 

Easy to install Kit comes complete with 8 each 4164N-20 (200ns) 64K 
Dynamic RAMs and documentation lor conversion Converts TRS-80 Color 
Computers with D. E. ET, F and NC circuit boards to 32K Also converts 
TRS-80 Coloi Computer II to b4K Fie* DOS or OS " required ],;, utilize 
lull 64K HAM on all computers. 

TRS-64K-2 $29.95 




4jSLs^5d£-i^5 



PROTECT YOURSELF... 

DATASHIELD 
Surge Protector 

Uiminales voll.tiju ';pik.---,.iti<i E MI-RFI noise hetor 
can damage your equipment or cause data lOH 6-S 
warranty Power dissipati 
2.000.000 watts 



PART NO 


DESCRIPTION 


PRICE 


MODEL 75 


4 Sockets, On/Off Switch 


. $49.95 


MODEL 85 
MODEL 100 
MODEL 110AMS 


6 Sock , Super Filters. On/Oft Switch. . 
6 Sock . Super Filters. Low Volt Alarm. 
6 Sockets. Super Filters, 
Auto Master Switch 


S59.95 
. $69.95 

$99.95 






DATASHIELD 
Back-Up Power Source 

Protect your computer trom black-outs. Brown out- power 
surges and line noise PTI's PC200 is ilesionrd tor PCs 

wilh floppy disk ni.< r, the «: : (0i: Iki hard i!r> in,-m,-,r v 

and iho AT800 lot mulli user systems A typical compatible 




PC200 (200 Watt Rating) 

XT300 (300 Watt Rating). 

AT500 (500 Watt Rating*. 

AT800 (800 Watt Rating) 



S299.95 
$399.95 
S699.95 
$799.95 



j£ Intelligent 300/1 200 Baud 
Prometheus Telephone Modem with 
Real Time Clock/Calendar 

The ProModem'" is a Bell 21 2A (300/1 200 baud) intelli- 
gent stand-alone modem ■ Full featured expandable 
modem • Standard features include Auto Answer and 
Auto Dial, Help Commands, Programmable Intelligent 
Dialing, Touch Tone"" and Pulse Dialing & More • Hayes 
command set compatible plus an additional extended 
command set- Shown w/ alphanumeric display option. 
Part No . Description price 

PM1 200 RS-232 Stand Alone Unit $349.95 

PM1200A Apple II, II+ and lie Internal Unit $369.95 

PM1200B IBM PC and Compatible Internal Unit $269.95 

PM1200BS IBM PC & Comp. Int. Unit w/ProCom Software $319.95 

MAC PAC Macintosh Package $399.95 

{Includes PM1200, Cable, & ProCom Software) 

OPTIONS FOR ProModem 1200 

PM-COM (ProCom Communication Software) $79.95 

Please specify Operating System. 

PM-OP (Options Processor) $79.95 

PMO-16K (Options Processor Memory - 16K). $10.95 

PMO-32K (Options Processor Memory - 32K) $20.95 

PMO-64K (Options Processor Memory - 64K) $39.95 

PM-ALP (Alphanumeric Display). $79.95 

PM-Special (Includes Options Processor, 64K Memory 

and Alphanumeric Display) S 189.95 



KEYBOARDS 





mm* 



13VLx4VWx VH 



New! 





SPECIAL 
FUNCTIONS! 

Description 



Mitsumi 54-Key Un en coded 
All-Pur pose Keyboard 

• SPST keyswitches • 20 pin ribbon cable connec- 
tion • Low profile keys ■ Features: cursor controls, 
control, caps (lock), function, enter and shift keys 

• Color (keycaps): grey • Wt.: 1 lb. * Pinout included 

KB54 $14.95 



5V4" APPLE™ 

Direct Plug-In 

Compatible Disk Drive 

and Controller Card 

The ADD-514 Disk Drive uses 
Shugart SA390 mechanics- 143K 
formatted storage • 35 tracks 
• Compatible with Apple Control- 
ler & ACC-1 Controller • The drive 
comes complete with connector and cable - just plug 
into your disk controller card ■ Size: 6"L x 3VW x 
8-9/1 6"D • Weight: 44 lbs. 

ADD-514 (Disk Drive) $169.95 

ACC-1 (Controller Card) $ 49.95 

More Apple Compatible Add-Ons... 

APF-1 ICooling Fan with surge protection). . . . $39.95 

KHP4007 (Switching Power Supply) $59.95 

JE614 (Numeric/Aux. Keypad for lie) $59.95 

KB-A68 (Keyboard w/Keypad for II & IN ) $79.95 

MON-12G 02" Green Monitor w/swivel stand). . . . $99.95 

JE864 (80 Col -64K RAM for He I $99.95 

ADD-12 (5V Half-Height Disk Drive). $179.95 

.^kAi^ 

JPfflL ADDITIONAL APPLE 
"lijjpT ADD-ONS AVAILABLE 

ARC-1 6K(16K RAM Card for Apple II fill + ) $39.95 

AEB-2 IEPROM Burner for Apple II. II • & He) . .$69.95 

Allows copy of standard EPROMS 

2708.2716. 2732, 2764 
ASSC-P (Super Serial Card for Apple II. II + & lie) . .$99.95 
ADD-IIC (5V Half-Ht Disk Drive for Apple lie) $189.95 



DISK DRIVES 



82-Key ASCII Cherry Keyboard 

■ 7-bit parallel ASCII ■ 1 1-key numeric keypad 

■ Cursor keypad ■ SPST mechanical keyswitches 
- 4 illuminated keys * 26-pin header connector 
Color white -Size 18"L x 6VW x 1 VH -Spec 

I n i Ilk1i.h1 



KB8201. 



. (1700 avail.}. . . . $29.95 



Apple Keyboard and Case 
for Apple II and II+ 

Keyboard * 68 keys • 15-key keypad ■ Direct con- 
neclion with 16-pin ribbon connector • 26 special 
functions • Size 14VL x 5VW x 1 VH 

Case: Accommodates KB- A68 • Pop- up lid tor easy 
access ■ Fits power supply and motherboard too 
• Size 15VW x 1S"D x 4VH Price 




Documentation % 1 8 U ^. 

Included ^^ ys/ 

MPI51S (MR 5U " SS full-ht.) $ 89.95 

RFD480 (Remex 5% " DS full-ht.) $109.95 

TM100-2 (Tandon 5V DS full-ht.) $159.95 

FD55B (Teac 5' 4 " DS half-ht.) $149.95 

SA455 (Shugart 5 V DS half-ht). ... $1 59.95 

FDD100-8 (Siemens 8" SS full-ht.) $119.95 

PCK-5 (5V Power Cable Kit) $2.95 

PCK-8 (8" Power Cable Kit) $3.95 



UV-EPROM Eraser 



KB-EA1 Apple Keyboard and Case (pictured above). .... $134.95 

KB-A68 68-Key Apple Keyboard only $ 79.95 

EAEC-1 Expanded Apple Enclosure Case only. .....$ 59.95 



POWER SUPPLIES 



Power/Mate Corp. REGULATED POWER SUPPLY 

•Input: 1O5-125/210-25OVACat47-63Hz ■ Line regulation 0.05% -Three 
mounting surfaces ■ Overvoltage protection ■ UL recognized ■ CSA certified 
Part No. Output Size Weight Price 



8 Chips - 21 Minutes 




1 Chip- 15 Minutes | 





*©i 




W 



EMAS/6B 
EMA5/6C 



5V'« ; 3A/6V<a2.5A 
5Vi.n<6A/6V!S'5A 



4V'Lx4"Wx2VH 
5VLx 4VWx2V'H 



2 lbs 



$29.95 
$39.95 



■ r. i ',.■.,: i: i PROM . m : ,..", 1 1 1 in ri chips within 2 1 minutes (1 chip 
in 1 5 minutes) Maintains constant exposure distance o) one inch 
Special conductive foam liner eliminates static build-up Built-in 
safety lock to prevent UV exposure. Compact - only 9 00"L x 
3.70"W x 2 60"H Complete with holding tray tor 8 chips 

DE-4 UV-EPROM Eraser. ..... $74.95 

UVS-11EL Replacement Bulb $16.95 



JE664 EPROM PROGRAMMER 



KEPCO/TDK 4-OUTPUT SWITCHING POWER SUPPLY 

• Ideal for disk drive needs of CRT terminals, microcomputers and 
video games • Input 1 1 5/230VAC, 50/60HZ • Output t-5V©5 Amp, (■ 1 2V § 
1.8 Amp. • 12V «d 2 Amp, -12V <o> 0.5 Amp • UL recognized • CSA certified 
•Size: 7VLx6-3/16"Wx1VH -Weight: 2 lbs $59 g 5 each Qr 

MRM 174KF 2 for $99.95 



Switching Power Supply for APPLE II, II+ & //e™ 

■ Can drive four floppy disk drives and up to eight expansion cards 

■ Short circuit and overload protection • Fits inside Apple computer 

* Fully regulated t 5V @ 5A, + 12V® 1.5A, -5V @ ,5A. -12V @ 5A 

• Direct plug-in power cord included ■ Size: 9VL x 3VW x 2'V'H 
•Weight: 2 lbs. 

KHP4007 (SPS-109) $59.95 



4-CHANNEL SWITCHING POWER SUPPLY 

• Microprocessor mini-computer, terminal, medical equipment and process 
control applications ■ Input: 90-130VAC. 47-440HZ -Output: +5VDC § 5A. 
-5VDC 6 1 A. + 1 2VDC 6 1 A. - 1 2VDC § 1 A • Line regulations. 0.2% • Ripple: 
30mV p-p • Load regulation: • 1% • Overcurrent protection ■ Adj 5V main 
output ' 10% -Size: 6VL x 1VW x 4-1 5/1 6"H ■ Weight: 1 <-2 lbs 

FCS-604A $69.95 



IBM PCXT EQUIVALENT 130 WATT POWER SUPPLY 

UPGRADE YOUR PC! 

■ Input; 100V-130V/2OOV-260V selectable @ 47 to 63Hz • Output: 
+ 5VDC @ 1 5A. -5VDC @ 0.5A, +1 2VDC @ 4.2A, 1 2VDC @ 0.5A 
• Plug compatible connectors • Fits into IBM PC • Weight: 6 lbs. 

IBM-PS $169.95 



See Our New IBM 

Communications 

Program! 




$10.00 Minimum Order — U.S. Funds Only 
California Residents Add 6Vi% Sales Tax 
Shipping — Add 5% plus $1.50 Insurance 
Send S.A.S.E. for Monthly Sales Flyer! 



Spec Sheets — 30* each 
Send $1.00 Postaqe for your 
FREE 1985 JAMECO CATALOG 
Prices Subject to Change 




B 



Ifffl! 



m* 



W^ r— 



ameco 



ELECTRONICS 



VISA" 



1355 SHOREWAY ROAD, BELMONT, CA 94002 
4/85 PHONE ORDERS WELCOME — (415) 592-8097 Te/ex: 176043 



REQUIRES NO ADDITIONAL SYSTEMS FOR OPERATION 

Programs and validates EPROMs * Checks for properly erased EPROMs 
• Emulates PROMs or EPROMs ■ Loads data ffi RAM by keyboard • Changes 
data m RAM by keyboard ■ Loads RAM trom an EPROM ■ 664 RAMs can be 
used tor external microprocessor development • Compares EPROMs for 
r i .nirni differences • Copies EPROMs ■ Input 1 1 5VAC «> 60Hz ■ Assembled 
and tested • Si2e 1 5VL x SVDx 3VH ■ Wt 5% lbs • 271 6 Module included 

JE664-A EPROM Programmer $995.00 

JE665-RS232C INTERFACE OPTION - This option implements computer 

■ '(., ,| : i,.j4 >;HAM .llluwili;;.. ruri|,;jhT I;.. III. ,' n; Hil.lN ■. Stnr.' , u l< I '1,'int- 

fef EPROM data to and from the JE664 Sample program listing is supplied in 
MBASIC for CP/M computers ■ Documentation provided to adapt the software 
to other computers with an RS232 port ■ Specs 9600 Baud. 8-bit word, odd 
parity with ? stop bits ■ Assembled and tested - 2716 Module included 

EPROM Programmer 
JE664-ARS w/JE665 Option $11 95.00 



JE664-ARS COMMUNICATION PROGRAM 
For IBM-PC or XT and Compatibles 



(..si .-ominlfr) BASK i.iHjj.im ■ Easy to use, menu-driven ■ Prim hard- 
copies of EPROM data ■ View data in HEX and ASCII NEW! 

The JE664-ARS Communication Program was written lor quick interlacing 
between the JE664-ARS EPROM Programmer and the IBM-PC computer and 
compatibles Menu-driven program allows user to Load and Save EPROM 
data to and from the coiiinuvi ■' fli-.j>j-.y Misk D,ii.i i mIciui) t>v tin ■ :ir.|.ui.:' 
cm be ni'wi'il in Hex * ASt :ll form..it=; Prinli'd narrl i i '|>i.:s arc- also displayed 
in both formats Program is ideal for keeping archives ol master EPROMs on 
disk The program is compatible tor all EPROMs listed with the JE664 
Computer requirements IBM-PC. XT (or eg I with at least! 28K RAM and one 
■ ■■. ii |ji,it piiunal .Jni! p.iiallel port tnr pi ntet 

JE664-ARS-CP $49.95 

JE664-ARS Communications Program (5 V Disk and User's Instructions) 

JE664-CP CABLE $29.95 

Cable for IBM-PC to JE664-ARS Program (5 Shielded Cable & Connectors) 



JUMPER (Personality) MODULES J jn ,, .. ■■ ,p f .(M,n.ilit-/: Mm! jl. ■. 
16K. 32K, and 64K EPROMs "Please specify EPROM and manufacturer 
JUMPER (Personality) MODULE ' 



les lor 8K, J 
facturer § 
95 each A 



Inquiry 2I2 



APRIL 1Q85 • BYTE 77 



Inquiry 158 



FRIENDLY COMPUTER 



■ CONDIT ION w.rl- 



FRIENDLY SERVICE AT A FRIENDLY PRICE 

Friendly Computer Center, Inc. 

1381 Coney Island Avenue. Brooklyn, New York 1 1230 



C ITOH PROWRITER 
ALL AVAILABLE w/I.B.M ROM 

7500 105 C P S . .. 219.00 
8510 120 C PS 289.00 
1550 120 C PS- 15' 449.00 
8600 180 C P S 569.00 

STARWRITER 

F-10-40P 849.00 

A-10-20 479.00 



PRINTERS SPECIAL' 
OKIDATA 

Microline 84-200 C P S 669.00 

Microline 82-120 C.P S 225.00 

Microline 92 359.00 
Microline 92 w/Mac 

Compatible , 459.00 

Microline 93 589,00 




IBM 



IBM- HARD DISK SYSTEM 
IBM* PC256K 
10 MEG W/1 DS FLOPPY 
IBM MONO CARDS MONITOR 



$3249 



omplete 




DISK DRIVES FOR IBM 



Teac '. ht DS/DD 
Rana2000 IBM 



'49 



ADD ON BOARDS 

FOR IBM 

AST Six Pack Plus 64K 249.00 
Quadram Expanded Quadboard 
w/64K . 259.00 

Hercules Graphics Board 319.00 
Hercules Color Card w/Parallel 
Port . . 1 79.00 

Koala Speed Key System 149.00 
Mouse Systems Mouse w/Mouse 
w/PC Paint and Menue 159.00 
Hayden Sara gon III Chess 34.90 
Microsoft Flight Simulator 1137.90 
Hayden Saragon III for Mac 39.90 

De Base III 349.00 

Framework . . 379.00 

SYMPHONY CALL 

Star Acounting Partner 2 749.00 
Wot d star 2000 24900 



SUPER SPECIALS! 



TOSHIBA 

New Toshiba- 1340 
Toshiba-1351 

Juki 

Juki-6100 
Juki-6300 
Juki Tractor 6100 . 

New Gemm SG Series 



699.00 
1 249.00 

379 00 

call 

109.00 

Call 



MODEMS 

Hayes 1200B IBM 
Hayes 1200 RS232 
Hayes 300 RS232 
Micromoden HE 
HAYES 300 -for lie 
New Hayes 2400 



379.00 
459.00 
195.00 
235.00 
239 DO 
CAII 



PRENTICE POPCOM 

1200 Exlernal 34900 

120 fnternal 32900 

CompuServe Starter Kit 28.95 

The Source Starter Kit CALL 
Grappler Bufterd Plus 16K 

w/cable 149.00 



LETTER QUALITY PRINTERS 

ONE TIME SPECIAL' iwited quantity 
C ITOH - Leading Edge25cps 
15' Daisy Wheel 



$449 



C ITOH Tractor 



129 O0 




Peripherals by Apple 

Apple Drive lie J289 
Apple He Mouse 

paint 
Apple lie Mouse with 

paint S139 

Apple 1200 '300 Baud v^ 

Modem $389 

APPLEWORKS tor he or 

He $219 

Apple He Professional System 

• Apple He 128K Compuler 

• Apple Dual Disk Drive 
w/controller ■ card 

• Apple Extended 80 column 
Display Card 

• Apple Monitor II - 12' tilt'green 

• Pro-Dos Operating System 

Special $1439 
Apple lie with Monitor and Stand 
Mac -Mania Special $975.00 
Macintosh 512K with Imagewnter 
Special $2649 



MONITORS 

Princeton HX-12 Graphics 459.00 

New Amdek Color 300 269.00 

Amdek 310A 175.00 



TAXAN 

T115 12 "Green 
T116 12' Amber ... 
T127 12 Green t.B.M 
T122 12" Amber IBM 
210 RGB Color . . . 



H9O0 
12900 



159O0 
259 00 



FOR MAIL OflKRS: Send Money Order Certified Check. Mastercard VISA gladly accepted Add estimated price for 

shipping, handling and insurance WE WILL SHIP ORDERS AT THE ADVERTISED PRICES GUARANTEED UNTIL aprii 30 85 

Appla is a registered Irademark of Apple Computer, inc. IBM is a registered trademark of International Business Machines 



sag (800) 258-5805 | (718) 252-9737 

eg Friendly Computer Center, Inc. r 

1381 Coney Island Avenue Brooklyn. New York 1 1230 



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COMPUTERS INC. 



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WORD PROCESSING 

Word Star 2000 
WordPerfect 4.0 
Volkswriter Deluxe 
PFS: Graph 
PFS: Write 
Easy writer II 

DATA BASE 

MANAGEMENT 

Knowledgeman 

dBase II 

dBase III 

Friday 

Pfs: File report pk 

R: Base 4000 

Quikcode II 

Infostar 

SPREADSHEETS 

Framework 
Multiplan 
Supercalc 3 
Visicalc IV 
Thinktank 
Calcstar 
TK Solver 



WE SHIP 
OVERSEAS 

TEL:(415) 340-1006 

851 Budway Road No. 303 

Burlingarne, CA 94010 
U.S.A. Telex 470477 Mons 

ACCOUNTING 

$264 IUS GL/AP/AR ea $295 



252 
169 

84 

84 

195 



275 
286 
369 
179 
162 
295 
155 
282 



369 
124 
199 
172 
109 
87 
269 



Peachpak 4 249 

Open Sys. ea 399 

State of Art ea 399 

BPI AR/AP/GL ea 395 

Great Plains Software ea 479 

HOME & RECREATION 



The Print Shop 
Bankstreet Writ. 
Dollars & Sense 
Fit Simulator 
Facemaker 
MindProber 
Mastertype 
Zargon II 



34.99 
49.99 
64.99 
35.00 
23.99 
36.99 
29.99 
16.99 



SPECIALS 




Sidekick (pro) 




37.99 


Sidekick (unpr 


o) 


54.99 


Turbo Pak: 




74.99 


Pascal-Tutor 


-Toolbox 


Taxadvantage 




49.99 


64K/9 chips 




25.99 


Paperback Wr 


tei 


29.99 


Executive Writer 


54.99 



Payment: Mastercard, Visa, COD, Money Order or Check. Pur- 
chase Orders welcomed from qualified institutions. Prices subject 
to change. No surcharge for Visa/Mastercard. Shipping UPS sur- 
face per item $4.00 within USA. Calif. Residents add sales tax. 



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tially beneficial application of computers. Schools should 
be paying attention to computers not because they will 
take over our lives or because everyone has to be a pro- 
grammer but because computers are part of the solution 
to education problems. 

The Future 

Computers will be really useful to the average person only 
when they can be used with no training at all. Schank sees 
advisory systems in areas such as finance, medicine, and 
law becoming available within the next few years. Sophis- 
ticated learning systems, with cognitive abilities, will be 
available within a decade, Schank says. And within 50 
years, he predicts, there will be integrated world-knowl- 
edge systems capable of learning about new domains; 
their most effective role will be as librarians and con- 
sultants, figuring out what we need to know about a sub- 
ject and the right way to explain it to us. 

Al may change the way we look at ourselves. One of 
its by-products will be the opportunity for an informed 
public. People lack the information they need because 
they don't want to appear stupid, bother an expert, or pay 
lots of money for advice. In the future, people will be able 
to obtain expert advice of all kinds, easily quickly, and 
inexpensively from computers. Of course, we should 
evaluate computer advice as carefully as we would that 
from any other advisor with a stake in our decision. 

Criticism 

Schank is best, and worst, when hypothesizing. He has 
made a career out of playing mind games, and most of 
those he presents are fascinating. However, he occasion- 
ally slips into an overly optimistic view of computers and 
the future. He says that machines will take over the most 
unpleasant human jobs and will provide people with the 
information they need to run their daily lives. I think this 
will be more a function of what people seek rather than 
simply what computers can provide. 

Audience 

The Cognitive Computer is not for those people who are in- 
terested in the engineering behind Al programs. Schank 
does not include details on how Al programs go together, 
what languages they are written in, and what kinds of hard- 
ware they run on. His contribution is to put thinking com- 
puters in perspective and show us where we can go with 
them. 

It is a credit to his science of understanding how humans 
understand that Schank writes with such clarity He dem- 
onstrates a genuine concern for how computers and their 
Al software will affect human lives, Schank has a healthy 
perspective on scientific progress: he doesn't believe that 
every aspect of human thought can or should be modeled 
on computers. ■ 

Darrow Kirkpatrick is an applications engineer at Development 
Associates Controls (POB 1049, Carpinteria. CA 93013). 



78 



BYTE • APRIL 1985 



Inquiry 360 



\bu can buy a 

less expensive diskette 

and not save a thing. 



One can understand the temptation to buy a less 
expensive diskette. 

Rather than a Dysarf diskette. 

After all, the less expensive diskette is probably 
almost as good. And should you run into a bad one, 
well, it didn't cost that much, anyway 

Right? Not quite, 

\bu see, a less expensive diskette is by definition 
less diskette. And the few pennies you save are worth 
a great deal less than what you have to lose. 

Namely, your data. 

That's why it makes more sense to spend a bit more 
for a Dysan diskette. 

Every Dysan diskette you buy will record and 
retain all your data all the time. 

"feu can be sure of that because every 
Dysan diskette is certified 100 percent 
error free and backed by our lifetime 
warranty* 



So next time you're tempted to buy a less expensive 
diskette, ask yourself this question. 

Can you really afford it? 

For the name of the Dysan dealer nearest you, call 
toll free (800) 551-9000. 

Dysan Corporation, 5201 Patrick Henry Drive, PO. 
Box 58053, Santa Clara, CA 95050. 



Dysan 



Inquiry 131 



Somebody has to be better 
than everybody else. 




' Warrant) details are inside even Dysan box. 
Dysan is a registered trademark of Dysan Corporation. 
1985, Dysan Corporation. 

APRIL 1985 • BYTE 



Give people the tools they need, 
and there is no limit to what they achieve. 



Announcing the first major 
breakthrough in word processing 
technology since WordStar. 

Now, state-of-the-art 
comes easy. 



Introducing WordStar 2000, a totally new 
word processing program from the makers 
of WordStar. 

WordStar 2000 removes all limits from 
word processing. From what you can create. 
From what you can achieve. 

Because WordStar 2000 lets you do 
everything. 

Easily. 

From windows, to undo, 
to spelling correction, WordStar 2000 
does it all. And more. 

WordStar 2000 gives you the works. 

"Windows" allows you to work on different 
documents— simultaneously. "Undo" lets you 
replace text you mistakenly removed. A built-in 
spelling corrector checks and corrects mis- 
spellings from over 97% of the most commonly 
used words. 

WordStar 2000 also has a "typewriter 
mode" to fill in forms or envelopes easily. Plus 
"format sheets',' which give you ready-made 



headings, tabs and margins at the touch of one 
key It can even create and update footnotes. 

Finally, a truly integrated 
word processing system. 

WordStar 2000 goes well beyond words. 

It comes with a built-in five function math. A 
built-in mail merge enables you to mass produce 
form letters. Get our special Plus package and 
you also get a built-in mail list data base that 
allows you to create, update and sort your own 
mailing lists. Also a built-in indexer. Not to 
mention built-in telecommunications capabilities. 

All integrated together, so you never have 
to leave the program. 

The only word processing program 

that interacts with you on your level, 

whatever your level. 

Before we created WordStar 2000, we studied 
the way people worked, and thought. We also 
drew from our experience with over 1,250,000 
WordStar owners. 



80 B YTE • APRIL 1985 




As a result, the keys you 
press are the keys you'd expect to press ("c" for 
copy, "p" for print, etc.). You may also use your 
computer's function keys. Menus have been 
uniquely designed for easy access to all functions. 
And MicroPro's exclusive "tutor-in-your- 
computer™ " makes learning fast and fun. 

WordStar 2000 is the easy word processing 
program you'll never outgrow. Of course, the 
original WordStar and WordStar for PCjr will con- 
tinue to provide substantial and proven word 
processing capability for those with more modest 
budgets. 

See your local MicroPro dealer today or call 
(800) 227-6703 [in CA (800) 632-7979] for the 
dealer nearest you. 

So you can remove all limits from what you 
can achieve. 



WORDSTAR 




Now available for IBM PCVATVXT* and compatibles with 256K 
RAM. Upgrade from WordStar to WordStar 2000 through your dealer, 
or call MicroPro Customer Update (800) 2275609, 9am-3pm P.S.T. 



Now there are no limits 1 : MicroPro. 



Inquiry 412 



APRIL 1985 'BYTE 81 




I weni ro look or rhe MBC -550 
nexr day' 



A<haM found mode me on owne' 're 
Dill SudbnnK Byre Mag a. 



A Custom 

System For 

Less Than a 

Clone 

TM 
The Silver Fox will run mosr of rhe 
I best-selling programs for rhe IBM-PC like 
rhe PFS series Wordstar Mulnplon d BASE II 
Flight Simuloror and Lorus 1 2 3 

But rhe basic Silver Fox gives you more 

I hardware rhan other 8068 systems including 

256K of PAM. 4 video ourpurs a 1 2" high- 

resolunon monitor a full 25x80 display 

I and o superior keyboard with a big rerurn 

key 

Also included as srandord equipment is 
rhe besr free software bundle m rhe business 
including 



MS-DOS 2 1 1 


HAGEN-DOS 


Color BASIC 


GV BASIC 


Wordstar 3 3 


Eosy Writer 


Spell 


Mail Track 


FILEBASE 


PC File ill 


CalcSrar 


Games Graphics 


PD Disk 


OS Tutor 



Bur rhe big feature rhe IBM-PC and its 
clones can't march is rhe Silver Fox 1 6 
mega byres of storage Even though the 
Silvet Fox drives can store more rhan twice 
as much information rhey can also read 
and write ro standard 160K. 320K and 
360K formats 

Because rhe Silver Fox is born on a 
totally automated line in Japan, it is simply 
mote telioble rhon PCs that are assembled 
by hand 5o we bock each Silver Fox with a 
1 1 mired one year warranty 

If you didn't think your 

$1397 

would buy you this much computer simply 
dial 

1-600-FOfWOX 

and leave your name ond address at rhe 
beep. We'll rush you our Silver Fox catolog 
that will tell you how ir can 



PRINTERS 




Epson FX-SO -^£$180 off 

Epson 

F0v-80FT ... -^^$100 off 

Tolly Spirit 80 $254 

Okidara 925*^ $125 off 

Okidara 935PPte ... $210 off 

Okidara 84 Coll 

SrarSG-10 $229 

SrarSIVl5 $599 

Dataproducts 

8050 loaded' $1344 

Tolly 160L $589 

Panasonic 1091 $298 

Toshiba 1040 $695 

Toshiba 1351 . $1198 

LETTER QUALITY 

Powerrype $299 

| Juki 6100 $389 

Juki 6300 .... $719 

Silver Reed 400 $249 

Silver Reed 500 $299 

Silver Reed 550 $409 

Silver Reed 770 $724 

NEC's Call 

Daisywrirer 2000 $824 

Diablo 620 $715 

Diablo 630 API $1499 




• IfW ff lf l^ i C ^Mitt 



ITU" 



* More Free Software * 

Along with all the free greor software you get with a Sanyo MBC 
550 Scottsdale Systems includes 3 extra disks with ( 1 ) OS Tutot- 
Teachesyou everything you need ro know about rhe operating sysrem 
right on your system (2) 1 5 gomes for rhe Sanyo 550 a S2° (retail) 
value (3) Daremare an appointment keeper with a perpetual 
calendar (4) IS Manager Allows you to change the structure of 
existing InfoStar files (5) PC File (6) 10 public domain gomes (7) 
diagnostics ond utilities and (8) Sketch A graphics/ drawing program 
Tirren m Sanyo Color Graphics BASIC 



©Sanyo 555-2's 



i ( vou plan ro purchase a Sanyo MBC 555-2 or a single drive MBC 550 2 
>ou ve made on exceHenr choice The Sanyo MBC 550 series is the 
"jwest priced 8068 MS DOS sysrem bar none Plus with the single dtive 
55G 2 sysrems you receive MS DOS 2 1 1 Sanyo Color Graphics BASIC 
^'ordsrar 3 3 CalcSrar and Easy Writer I 

Wirh rhe 555 2 sysrems you also receive your choice of DoraSrar 
,J -eportStor SpellSrar and MailMerge or Easy Wnrer II Easy Mailer Fasy 
Planner and Easy Filer 

We have sold more Sanyo microcompurers rhan any orher dealer 
n the United States Our prices have also been the lowest or among 
•he lowest in rhe country ond are presently too low to advertise 

Bur we wouldn r have became the largest Sanyo dealer in rhe 
:>unrry if all we offered was low prices We include more free softwate 
•han orher dealers we con install boards or extra memory for o modest 
natge and we stock tefetence manuals for out customers 

Our soles staff knows rhe Sanyo system because rhey use Sanyo 
omputets themselves and unlike others who sell the Sanyo system 
A-e re on authorized Sanyo service center with techs on staff if you plan 
ro buy o Sanyo give us a call we II offer you a great price and o gieor 
deal more 




Columbia's 



I If you re looking for maximum compatibility 
n prices ond nationwide service you 

I should consider buying o Columbia from 
Scorrsdale Systems Eoch system comes with o 
huge software bundle including MS-DOS 2 1 
Basica Perfecr Writer Perfect Calc Perfect 
Filet. Perfecr Speller Fost Graphs Home 
Accountant Plus Space Commanders ATI 

I Tutorials and T.I M. IV We have the lowest 

| prices on all Columbia computers including 
the new 4220 desktop with 256K 2220 

I portable with o built-m 9" monitor Your 



choice 



$1698 



While they last 

complete systems 

Sanyo 1100s 



Our lowesr price ever on o complete duol 
dtive system Each Z80 based Sanyo 1 1 system 
includes builr-m 320K (formatted) disk drives a 
cooling fan a built-m 1 2" 25x80 green phosphor 
momrot a parallel port and a senal port ond o 
great keyboatd wirh 1 5 special funcnon keys 
'enabled under both WordStar and BASIC) ond 
o bulir-in palm resr 

Plus eoch sysrem comes wirh CP/M Sanyo 
BASIC ond o complete MicroPro series of software 
including Wordstar 3 3 MailMerge SpellSrar 
DaroSror PeporrSrar and CalcSrar We pretesr 
each sysrem. and rhey re backed by over 75 
service cenrets nationwide 

As someone who wrore us pur it My local 
dealer says you couldn t possibly sell this whole 
package for 5888 because he sells rhe WordStar 
alone for $495 

Well rhe local deoler is pamally correct 
because while rhey last we re selling the whole 
package for 



SINCE 1980 



TELEMARKETING ONLY If you plan to visit please coll first for on appointment. Prices listed 
are for cosh and include o 3% discount We sell on o Ner 30 basis to Fortune 1200 | 
companies ond universities. No CO D s or A.P O s.POs odd 2%. Viso Mastercard add 3% 
Az residents add 6% Prices subject to change product subject to availability 
Petsonal/company checks take 3 weeks ro clear All items listed are new with I 
manufacrurets warranty. 0-20% restocking fee for returned merchandise Shipping extra- 
products ore F.O.D. point of shipment Software is not warronned for suitability Registered 
trademarks: Televideo-Televideo Sysrems Inc ; Stiver FoxTM HAGEN-DOS- Scorrsdale | 
Systems Ltd Com muter- Visual Computer Incorpotated 



Houstin Instruments 

DMP-29 51 795 

DMP-40 $745 

DMP-41 S2340 

L orher models coll i 





Altos Systems . . . big discounts, local installation 



Scorrsdale Sysrems m. 

617 N. Scorrsdale Road, Suite D, Scorrsdale, Arizona 85257 

~ (602) 941 -5856 [™ 

Coll 8-5 Mon.-Fri. 
A 

Jp^ We participate in arbitration for business and customers rhrough the Better 
Business Bureau of Maricopa County 



$848 



OLYMPIA IMP 



:W 




IS IT SICK TO 
LOVE A PRINTER? 

If you love your Okidara 92 or Epson FX-60 
don t read any further because the new 
Olympia NP is rated as faster is noticeably 
quiter and has a near letter qualiry mode 
-har is much superior ro anything in irs price 
■ lass 

Plus unlike the Okidata or rhe Epson rhe 
Olympia comes with adjustable ttactot 
f eed Cos well as friction feed) as standatd 
equipment The tractor feed is rhe push- 
type and rhe NP has a rear bar so rhar ir 
works grear with continuous ferns 

The NPuses Jandard Epson rype ribbons 
comes with the quality that has made 
Olympia a world leader m typewriters and 
is backed by nationwide setvice 

To quore PC magazine The ( NP ) printer 
is a sure rhmg if it falls into your price range 
and even if it doesn't it may be worth 
considering 

If you re considering rhe purchase of an 
Okidara an Epson, or even o Toshiba give 
us a call ond ler us send you an actual print 
sample from rhe Olympia NPand additional 
mformarion 

Because if you were ro buy an Epson 
FX-80+ or an Okidara °2 with rracrors at 
rhe lowesr advertised price anywhere you 
would be paying about $ 1 00 more for on 
inferior printer Scorrsdale Systems sells the 
Olympia NP wirh a 1 0' shielded cable for a 



$044 



82 BYTE- APRIL 1985 



EVENT QUEUE 



April 1985 



• BUSINESS SHOW 
Business-Expo, various sites 
throughout the U.S. This 
show features exhibits and 
services related to office 
technology. Contact Interna- 
tional Business Expositions 
Inc., 200 East Northland 
Towers, 15565 Northland Dr., 
Southfield, MI 4807 5-5378, 
(313) 569-8280. April-May 

• ROBOTICS, MATHE- 
MATICS, COMPUTER 
LECTURES-Robotics Lec- 
ture Series and Colloquium 
Series, Room W-117, Mathe- 
matics & Science Building, 
Montclair State College, 
Upper Montclair. Nj. Month- 
ly lecture series featuring ex- 
perts in computer science, 
mathematics, and robotics. 
Contact Gideon Nettler, 
Department of Mathematics 
and Computer Science, 
Montclair State College, 
Upper Montclair, Nj 07043, 
(201) 893-4294 or (201) 
893-5132. April-May 

• INTELLIGENT MACHINES 

Machine-Intelligence Classes, 
Turing Institute, Glasgow, 
Scotland. Among the classes 
offered are Foundations of 
Artificial Intelligence" and 
"Cognitive Modeling as a 
Basis for Expert Systems." 
Contact The Turing Institute, 
George House, 36 North 
Hanover St., Glasgow Gl 
2 AD, Scotland; tel: 041- 
5 52-6400. April-June 

• MEMORY CARDS 
STUDIED-Memory-Card 

Technology, Columbus, OH. 
Business, industrial, and 
technological concerns will 
be addressed. Panel discus- 
sions and exhibits. The fee 
is $495. Contact Phil Wells, 
Battelle Memorial Institute, 
505 King Ave., Columbus, 



OH 43201-2693, (614) 
424-7249. April 10-11 

• SYSTEMS DEVELOP- 
MENT AND FOURTH 
GENERATION— Structured 
Techniques Using Fourth 
Generation Languages, 
Chicago, 1L. This seminar ex- 
plains how to use fourth- 
generation languages in a 
structured systems develop- 
ment environment. Contact 
Digital Consulting Associates 
Inc., 6 Windsor St.. Andover, 
MA 01810, (617) 470-3870. 
April 10-12 

• COMMUNICATIONS 
TECHNOLOGY FOR THE 
NONVERBAL-The Fourth 
Annual Conference on Com- 
munication Technology: 
Technology and Nonspeak- 
ing Children, loseph Stokes 
Auditorium, Children's 
Hospital of Philadelphia, PA. 
Up-to-the-minute information 
on the use of technology 
with nonverbal children will 
be presented. Concurrent 
sessions will address on- 
going research, computers, 
and treatment strategies. 
The registration fee is $95. 
Contact Joan Bruno, 
Children's Seashore House, 
4100 Atlantic Ave., POB 
4111. Atlantic City. NJ 08404, 
(609) 345-5191, ext. 278. 
April 12-13 

• MAC IS FEATURED 

Mac Fair, Creese Student 
Center, Drexel University, 
Philadelphia, PA. Seminars, 
demonstrations, and ex- 
hibits. Student-sponsored. 
Contact MacFair, The 
DUsers, Creese Student 



Center, Drexel University, 
Philadelphia. PA 19104, (215) 
895-2 573. April 13 

• COMPUTERS AND 
PEOPLE-CHI '85: Human 
Factors in Computing Sys- 
tems, Hyatt Regency at 
Embarcadero Center, San 
Francisco, CA. Contact ACM 
Conference Management, 1 1 
West 42nd St., New York, 
NY 10036, (212) 869-7440. 
April 14-18 

• OPTICAL STORAGE 
INVESTIGATED-The 1985 
Materials Research Society: 
Symposium D, Golden Gate- 
way Holiday Inn, San Fran- 
cisco, CA. The mass-storage 
technologies symposium will 
investigate optical data 
storage. Areas to be ad- 
dressed include write-once 
and erasable media, read- 
only technology substrates, 
and lasers. Contact D H. 
Davies, Symposium Co-Chair, 
3M, 420 North Bernardo 
Ave., Mountain View, CA 
94043. April 15-18 

• SEMINAR CONSIDERS 
CAD— Computer-Aided 
Design, Ramada Inn, 
Rochelle Park, NJ. A seminar 
featuring PCAD and Auto- 
CAD products. Contact 
Compu-Sales Corp., 1096 
Goffle Rd., Hawthorne, NJ 
07506, (201) 427-5949. 
April 16 

• BUCKEYE SHOW 

The Ninth Annual Computer 
Fair, University of Dayton 
Arena, OH. Terminals, micro- 
computers, and word pro- 
cessors to be displayed. 



IF YOU WANT your organizations public activities listed in BYTE's Event 
Queue, we need to know about them at least four months in advance. Send 
information about computer conferences, seminars, workshops, and courses 
to BYTE, Event Queue, POB 372. Hancock. NH 03449. 



Contact Dan Schumacher, 
University of Dayton, 300 
College Park Ave., Dayton, 
OH 45469, (513) 229-3511. 
April 16-17 

• DBM AND FOURTH 

GENERATION-Database 
Management Systems and 
Fourth Generation Lan- 
guages for Personal Com- 
puters. Atlanta, GA. Topics 
include approaches for 
managing data, operational 
considerations, and manage- 
ment issues. The fee is 
$795, Contact Software In- 
stitute of America Inc., 8 
Windsor St., Andover, MA 
01810, (617) 470-3880. 
April 17-19 

• OFFICE, DP EQUIPMENT 

CeBIT '85, Hannover, West 
Germany. More than 1 300 
exhibitors from more than 
2 5 countries will display of- 
fice equipment and data- 
processing technology. Held 
in conjunction with the Han- 
nover Fair. Contact Han- 
nover Fairs Information 
Center, Route 22 East, POB 
338, Whitehouse, NJ 08888, 
(800) 526-5978; in New 
Jersey, (201) 534-9044. 
April 17-24 

• NETWORK CONTROL 
AND MANAGEMENT 
Network Management/ 
Technical Control, Marriott 
Copley Place, Boston, MA. 
Diagnostic and test in- 
struments will be among the 
products displayed. Contact 
Louise Myerow. Registration 
Manager, CW/Conference 
Management Group, 375 
Cochituate Rd.. POB 880, 
Framingham, MA 01701. 
(800) 225-4698: in 
Massachusetts, (617) 
879-0700. April 18-19 

(continued) 



APRIL 1985 • BYTE 83 



Inquiry 178 



HARMONY VIDEO & COMPUTERS 

2357 CONEY ISLAND AVE.. BROOKLYN. NY 11223 

800 VIDE084 OR 800-441 1144 OR 718-627-1000 





COMMODORE 64 




APPLE 2C 






$149.95 




$889.95 




,^M#~" 


APPL 




GEMINI SG 10 


<&t^ 




$839.95 




$215.95 








"PRINTER SPECIALS' 






Anadex 


',.! 


Epson FX 100 * 




Ok i mate 10 


127 


Brother HRi 5 XI 


349, 


Epson LQ 1500 


996 


Olympiaro 


304 


Brother HR 35 


777 


Gemini Sq 10 


216 


Panasonic KXP 1091 


255 


Brother Keyboard 


'."< 


Gemini SCi 15 


J5i 


Panasonic KXP 1090 


169 


! Citizen MSP 10 


329 


HP Laser Jet 2678 


Panasonic KXP 1092 


379 


Citizen MSP 15 


488 


Juki 6100 relevtdeo 


371 


Panasonic kxp 1093 


562 


Corona Laser 2369 


Juki 6300 


""■ 


Panasonic KXP 3151 


460 


Daisywnter 


■ •' 


Man nesman Spirit 80 


n.'..- 


Powertype 


279 


Delta SD 10 


352 


Mannesman 160L 


529 


Ouadjet 


' 


Delta SD 15 


431 


Mannesman t80L 


739 


Radu SB 10 


461 


Diablo620 API 


b/H 


NEC 2050 


t. ig 


Radix SR i r i 


570 


Dynax DX 15 XL 


342 


NEC 3550 1297 


RitemanBlue + 


226 


Epson RX 80 FT *- 


285 


NEC 7730 1 


629 


Silver Reed Exp 550 


378 


Epson RX80 


:.•>■ 


NEC 8850 1 


F,/'< 


Silver Reed Exp 500 


286 


Epson RX 100 


374 


■■> lata 92 




Silver Reed Exp 770 




Epson FX80 


■':<■: 


Okidata93 


564 


Toshiba 1340 
Toshiba 1351 


678 
1213 



WOW! WOW! WOW! 



Macintosh 
Apple 2C 



ATARI 

800 XL 
1027 Printer 
1050 Drive 
Indus Drive 
1025 Printer 



MODEMS 

Hayes 1200 
Hayes 1200B 
Hayes 300 
Micromodem 2E 
Access 123 



834 
1679 
887 

473 



IBM 

PC w/Dnve 

PC XT 

PC Portable w/Dnve 

AST Six Pack 

Tallqrass 20 Meg 

Quad Board 

Keytromcs 

Hercules Color 

Hercules Moii- u hron 

Per syst Color Card 

Persyst Monocard 

Planlronics 

PC wr 1 10 Meg Hard Df 

Bernouh Box 

10 Meg Drive 



ZENITH 

ithPC2i50 

nth PC 15152 
ithPCl6l 52 



1449 
306 ■ 
CALL 
239 
2 174 
224 
159 



409 

a m 

1 ■)<,., 

399 



MONITORS 

Tidek 300 Green 
mdek 300 Amber 
nber 



310A 
C..I-.F 300 
Color 500 
Color 600 
Color 700 
Color 710 
Taxan2l0 
Princton HX12 
Taxan 122A 
Taxan 420 



550 n s 
555 DS 
CRT 70 



COMMODORE 



800-441-1144 



1541 Disk I 
1702 Mom 
MPS 802 



Powerful Single Board Computer 
Includes CP/M Plus on Disk 




iw era 

i es the me. 1 popuiai rrw n pi 
/«0. as Us main C PU MSC ICO runs at 4 MH7 vwthoul 
any wait states Thewhole system is tncorpora 
Mifjriqii.ilJty four l.iye' I'' . ■ ,.r - .vv- ,, r u , only 145mm 

• -■'! iii>- system requirps only I : *\n \ 
M + 5 Volts and t Amps at + 12 Volts 

Banked CP/M Ploi Included 
i piM Plus [3.0 banked] n m. imied on disk witti all 
manuals cp/m Plus is upwardly compatible *nh cpim 
.' . up l i'ii luUf 1 1 ii' Sll !'(i'()NLjyci, thPMAf and RMAC 
macro assemblers and the LINK-80 loader MSC-ICOs 
uustom BIOS provides support for multiple disl ' irmai' 

• ■ ' i ■ n-i'i i.iitrul System spn iti. . .ti a .■■ 
'nrmatting. disk c.opy">f|. defining runct* n 
'■■ attributes rsalso included 

128Kb RAM 

One 64K bank Of memory is rtevocefl ro CP/M and its 

disl .!■ he bli ' w) Hi theothei W Pan! 

. ■■'■'• '„'! only 
provides mc i (rams, but rt significantly 

rncreases the speed of titsk Ifi 

Internal Floppy Oltk Controller 
larUANSI tan lard I 

>]nvf". Mi ,1 v.T !'■!■/ "I ■ l.-'i" .Tld tin inaf, 
•8 SSSD ,'43 Kb 
•8 DSDD, 1.2Mb 
• S 1(4 DSDO, 320Kb 
•S 1(4 DSOD, SOOKb 
■ S-1/4 QMD. 1.2Mb 

Up to tour drives of any density or sue can Pi 
netted toMSC ICO Both 5 1(4 and 8 men connectors are 
r. irdi ■" 

High Speed CRT Controller 

MSC-ICO contains an 80 * 24 Imp memory mapped CRT 
ntfotlei i ■ outpul composite or separate to 
: J- ■- r - 

line, reverse video, and semrgrapnu ■-. are 

< uivi' escapi i ■ ■ we an i ctensioi til Dl i ■ 
rwned to emulate i it 



^l ^ ^^ ^^ New Items: 

Includes CP/M A0 on rJs* *H 

Mountain Side Oomputer 

Video, 128Kb, CP/M Plus™, and more 



Two BS232C Ports 

MSi ICO cot . rtme , ploi 

■■.■■.■ 

grammabte foi baud rati • stO| bits, data formal and 

■ 

jumper Sele I 

Centronics Parallel Port 

A standard Cenironir s parallel port allows MSC ICO to 
tner ('j,iralirM iievrcr", 
Parallel Keyboard Port 

MSC-ICO connects to any ASCII parallel ki 

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Inquiry 431 for Dealers. Inquiry 432 for End-Users. 



EVENT QUEUE 



• COMPUTER FESTIVAL 

The Tenth Annual TYenton 
Computer Festival. Trenton 
State College, Trenton, N|. 
Talks, tutorials, user-group 
activities, exhibits, computer- 
graphics theater, games, and 
a 50-acre outdoor elec- 
tronics flea market are some 
of the highlights of this an- 
nual event. Contact Ms. 
Marilyn Hughes, Trenton 
State College, Millwood 
Lakes CN 5 50. TYenton, NJ 
0862 5, (609) 771-2487. 
April 20-21 

• AIDS FOR EDUCATORS 

AEDS/ECOO 85: The 
Twenty-Third Annual Conven- 
tion of the Association for 
Educational Data Systems 
fAEDS), Hilton Harbour Cas- 
tle, Toronto, Ontario, 
Canada. A forum for edu- 
cators to exchange ex- 
periences and to keep up to 
date on developments in 
educational computing. The 
theme is "Computing Knows 
No Borders." Co-hosted by 
the Educational Computing 
Organization of Ontario 
(ECOO). Contact AEDS/ 
ECOO '85, c/o OISE, 2 52 
Bloor St. W, Toronto, Ontario 
M5S 1V6, Canada; in the 
U.S., AEDS/ECOO '85. 1201 
1 6th St. NW, Washington, DC 
20036. April 21-27 

• CAD FOR ARCHITEC- 
TURE, ENGINEERING 

CADDMania: Causes and 
Cure, Sheraton TWin Towers, 
Orlando, FL. Techniques for 
computer-aided design and 
drafting for architecture and 
engineering. The fee for the 
full three days is $175; the 
daily rate is $100. Contact 
Pat Johnson, CEPA Inc. 
15713 Crabbs Branch Way, 
Rockville, MD 20855, (301) 
926-7070. April 22-24 

• SPEECH IN FOCUS 

Speech Tech '85, Vista Inter- 
national Hotel, World Tnade 
Center, New York City. 
Speakers and exhibitors will 
focus on voice synthesis and 
recognition. Registration is 



$195. Contact Media Dimen- 
sions Inc., POB 1121 Gracie 
Station, New York, NY 
10028, (212) 772-7068 or 
(212) 680-6451, April 22-24 

• DECISION-SUPPORT 
DISCUSSED— National Con- 
ference on Decision-Support 

Systems, Washington, DC 
Examines the implementa- 
tion and integration strate- 
gies of decision-support 
systems into management. 
T\vo days of workshops. The 
fee is $74 5. Contact Con- 
ference Manager, U.S. Pro- 
fessional Development In- 
stitute, 1620 Elton Rd.. Silver 
Spring, MD 20903, (301) 
44 5-4400. April 22-2 5 

• PUBLIC NETWORK 
OPERATIONS-X.25 and 
Packet Switching Networks, 
Atlanta, GA. This course 
covers the internal opera- 
tions of a packet-switching 
network and its implementa- 
tion. International standards 
are also covered. The fee is 
$795. Contact Elaine Had- 
den Nicholas, Department of 
Continuing Education, 
Georgia Institute of Tech- 
nology, Atlanta, GA 30332- 
0385, (404) 894-2 547. 

April 23-2 5 

• TRADE SHOW, CON- 

FERENCE-Electro/85 and 
Mini/Micro Northeast-85, 
New York City. Areas to be 
covered include artificial in- 
telligence, communications 
and networks, consumer 
electronics, high-density data 
storage and personal com- 
puting. Contact Electronic 
Conventions Management, 
8110 Airport Blvd., Los 
Angeles. CA 90045. (213) 
772-2965. April 23-25 

• COMPUTER APPLICA- 
TIONS EXPLORED 

Perscomp 85, Sofia, 
Bulgaria. An international 
conference on the applica- 
tions of personal computers 
and the problems en- 
countered in using them. 
Contact Dr. Marcel Israel, 



84 BYTE 



APRIL 198^ 



EVENT QUEUE 



Bulgarian Academy of 
Sciences, Institute of In- 
dustrial Cybernetics and 
Robotics, 113 Sofia, Acad. G. 
Bonchev St.. BI. 12. Bulgaria; 
tel: 72-46-98; Telex: 22836 
ITKR BG. April 2 3-26 

• EXPERT SYSTEMS 

Expert Systems and 
Knowledge Engineering, 
Gottlieb Duttweiler Institute, 
Ruschlikon/Zurich, Switzer- 
land. The theme is "Essen- 
tial Elements of Advanced 
Information Technology." 
Contact Dr. T Be mold, 
Gottlieb Duttweiler Institute, 
CH-8803, Ruschlikon/Zurich, 
Switzerland. April 2 5-26 

• MICROS IN EMPIRE 

STATE— The Fourth Annual 
New York Computer Show 
and Software Exposition, 
Nassau County Coliseum, 
Uniondale, NY. Contact Ann 
Katcef, Com pu Shows, POB 
3315, Annapolis, MD 21403, 
(800) 368-2066; in Annap- 
olis, (301) 263-8044; in 
Baltimore, (301) 269-7694; in 
the District of Columbia, 
(202) 261-1047. April 25-28 

• VIRGINIA COMPUTING 

The Fourth Annual Virginia 
Computer Show and Soft- 
ware Exposition, Pavilion, 
Virginia Beach. VA. Contact 
Ann Katcef, CompuShows, 
POB 3315, Annapolis, MD 
21403, (800) 368-2066; in 
Annapolis, (301) 263-8044; 
in Baltimore, (301) 269-7694; 
in the District of Columbia, 
(202) 261-1047. April 25-28 

• EQUIPMENT SALE 

Produx 2000: Wholesale 
Expo '85, Civic Center, 
Philadelphia, PA. Six hun- 
dred booths of computers, 
communications devices, 
and business equipment for 
sale. Contact Vertical 
Marketing Corp., POB 557. 
Bala Cynwyd, PA 19004, 
(215} 457-2303. April 26-28 

• SPRING WITH 
COMMONERS-COMMON'S 
Spring '85 Conference. 



Louisville, KY More than 
2 50 presentations are 
planned. Contact COMMON, 
Spring '85 Conference, Suite 
1717, 43 5 North Michigan 
Ave, Chicago. IL 60611, (312) 
644-0828. April 27 -May I 

• INTELLIGENT VISION 

Intelligent Vision Systems, 
Holiday Inn, Monterey, CA. 
The technical and marketing 
aspects of intelligent vision 
will be covered. Contact 
Richard D Murray, Institute 
for Graphic Communication 
Inc., 375 Commonwealth 
Ave, Boston, MA 02115, 
(617) 267-9425. April 28-30 

• INTRO TO UNIX 

Introduction to the UNIX 
System, Atlanta, GA. The 
pros and cons of UNIX will 
be covered. Contact Digital 
Consulting Associates Inc., 8 
Windsor St., Andover. MA 
01810, (617) 470-3870. 
April 29-30 

• C FOR ENGINEERS 

C Programming for Engi- 
neers, University of 
Michigan, Dearborn. A short 
course and workshop. Con- 
tact Professor R. E. Little, 
University of Michigan. 4901 
Evergreen Rd., Dearborn, MI 
48128, (313) 593-5241. 
April 29~May 3 

• KNOWLEDGE ENGI- 
NEERING— Knowledge Engi- 
neering: A Short Course, 
University of Tennessee 
Space Institute, Tullahoma. 
Contact Professor Moonis 
Ali, University of Tennessee 
Space Institute, TuIIahoma, 
TN 37388-8897, or call the 
Short Course Office at 
(615) 455-0631, ext. 278. 
April 29-Maw 3 

• COMMERCIAL Al, HIGH- 
TECH CONFERENCE-AI 

1985: Artificial Intelligence 
and Advanced Computer 
Technology Conference/Ex- 
hibition, Convention Center, 
Long Beach, CA. More than 
20 technical sessions as well 
[continued] 



"There's no magic to using 
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Fred Molinari, President 



There's no trick to it. 

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Our boards 

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And these boards just plug into the PC's backplane. 
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Comprehensive 
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IBM PC is a registered trademark of IBM Apple II is a registered trademark of Apple Computer Corp. Tl Profes- 
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Equipment Corp. COMPAQ is a registered trademark of COMPAQ Computer Corp. 



Inquiry 109 



APRIL 1985 -BYTE 85 



Inquiry 4 I 5 




New 64K SBC 

Only 

$ 375. 




4"x6" 

Requires no terminal. Includes 
Video Controller and CP/M® 2.2 

Runs any size floppy drive. 

Other models include Hard 
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128K or 256K RAM, and 8088 



64K SBC includes: 

• 6MHz Z80B 

• Video Controller 

• 2 Serial Ports 

• 4 Parallel Ports 

• I/O Expansion 

CPMisa registered 
trademark ot 
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• Source Code and Drivers 
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• CP/M'' 2.2 
Call our Toronto 
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Or write: Megatel 
1051 Clinton St., 
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14206 



— Substantial OEM Discounts Available 



EVENT QUEUE 



as panel discussions and 
product displays are 
planned. Contact Tower Con- 
ference Management Co., 
33 1 West Wesley St., 
Wheaton, IL 60187. (3 12) 
668-8100. April 1>0-May 2 

• MEETING ON LINE 
National Online Meeting, 
Sheraton Centre Hotel, New 
York City. On the docket are 
formal paper presentations, 
product review sessions, 
exhibits, and special work- 
shops and seminars trans- 
mitted via satellite. Contact 
Thomas Hogan, National 
Online Meeting, Learned 
Information Inc., 143 Old 
Marlton Pike, Medford, N] 
08055. (609) 654-6266. 
April 30-May 2 



May 1985 



• SUMMER SEMINARS 
Summer Seminar Series, 
Rochester Institute of Tech- 
nology, NY. A series of one- 
week seminars. Titles include 

introduction to Linear Sys- 
tems and Digital Signal Pro- 
cessing," "Basic 6800/6809," 
and "Advanced Digital 
Logic." Contact Yvonne Fish. 
School of Engineering Tech- 
nology Rochester Institute 
of Technology, One Lomb 
Memorial Dr., POB 9887, 
Rochester, NY 14623, (716) 
475-2915. May-\une 

• MICROELECTRONIC 
ENGINEERING 

Microelectronic Engineering 
Conference, Rochester In- 
stitute of Technology, NY. 
Technical papers and tours 
of microelectronic engineer- 
ing facilities. Contact Dr. 
Lynn Fuller, Microelectronic 
Engineering Program, 
Rochester Institute of Tech- 
nology, One Lomb Memorial 
Dr., POB 9887, Rochester. 
NY 14623, (716) 475-2035. 
May 1 

• SCIENTIFIC COMPUTING 
AND AUTOMATION-The 



First Scientific Computing 
and Automation Conference 
and Exposition, Convention 
Center, Atlantic City, N|. For 
practitioners and managers 
in analytic chemistry, bio- 
technology/biomedical 
research, clinical chemistry, 
and engineering. Product 
displays. Contact Expocon 
Management Associates Inc., 
3695 Post RcL Southport. 
CT 06490. May 1-3 

• SPECIAL EDUCATION 

SOFTWARE-National Con- 
ference on Special Educa- 
tion Software, Radisson 
Mark Plaza, Alexandria, VA. 
The theme is "DISCover the 
Possibilities." Product dis- 
plays and demonstrations. 
Registration; $50. Contact 
Elsa Glassman, The Council 
for Exceptional Children, 
Department of Professional 
Development, 1920 Associa- 
tion Dr., Reston, VA 22091, 
(703) 620-3660, ext. 261. 
May 2-3 

• COMPUTERS AND 
WRITING-UCLA Con- 
ference on Computers and 
Writing: New Directions in 
Teaching and Research, Uni- 
versity of California, Los 
Angeles. Contact Dr. Lisa 
Gerrard UCLA Writing Pro- 
grams, 371 Kinsey Hall, 
UCLA, Los Angeles, CA 
90024, (213) 206-1145. 

May 4-5 

• FAULT-TOLERANT 
DESIGN— Introduction to 
Fault-Tolerant Microcomputer 
Systems, Wisconsin Center, 
Madison, Presentations will 
emphasize practical applica- 
tions. The fee is $650. Con- 
tact William C. Dries, Univer- 
sity of Wisconsin-Extension, 
Dept. of Engineering and 
Applied Science. 432 North 
Lake St., Madison, Wl 
53706, (800) 262-6243; in 
Wisconsin, (608) 262-2061, 
May 6-8 

• INTEGRATED OPTICS 

ECIO '85: The Third Euro- 

[continued) 



8t> 



BY T E • APRIL 198S 



Inquiry 254 



THE PROFESSIONAL'S CHOICE 



Lotus 
1-2-3 

*299 



Lotus 
Symphony 

'419 



dBase III Framework MultiMate 

$339 '339 '259 



WordStar 
2000+ 

'319 



Software 

Word Processing Editors 

EASYWRITER II 

SYSTEM $219 

FANCY FONT $139 

FINAL WORD $189 

MICROSOFT WORD $239 
MICROSOFT WORD 

W/MOUSE $289 

MULTIMATE $259 

PFS: WRITE $ 95 

SAMNA WORD III SCall 
VOLKSWRITER 

DELUXE $159 
VOLKSWRITER 

SCIENTIFIC $309 
THE WORD PLUS 

(OASIS) $105 

WORD PERFECT $249 

WORDPLUS W/BOSS $319 

WORDSTAR $199 

WORDSTAR 2000 $269 

WORDSTAR 2000+ $319 
WORDSTAR 

PROFESSIONAL $259 

XYWRITE ll+ $229 

Spreadsheets/ 
Integrated Packages 

ELECTRIC DESK $209 

ENABLE $459 

FRAMEWORK $339 

LOTUS 1-2-3 $299 

MULTIPLAN $135 

OPEN ACCESS $299 

SMART SYSTEM $559 
SPREADSHEET 

AUDITOR $ 79 

SUPERCALC 3 $199 

SYMPHONY $419 

TK! SOLVER $259 

Desktop 

Environments 

DESK ORGANIZER $129 

GET ORGANIZED $159 

SIDEKICK $ 45 

SPOTLIGHT $109 

Communications/ 

Productivity Tools 

CROSSTALK $105 

PROKEY $ 89 

RELAY $ 99 

SMARTCOM II $109 



Database Systems 

ALPHA DATA BASE 

MANAGER II $179 

CLOUT V 2.0 $139 

CONDOR III $299 

DBASE II $269 

DBASE III $339 

INFOSTAR+ $319 

KNOWLEDGEMAN $269 
PFS: FILE/PFS: 

REPORT $169 

POWERBASE $219 

OUICKCODE III $169 

R BASE 4000 $259 

Languages/Utilities 

CONCURRENT DOS $189 

C86 C COMPILER $299 

DIGITAL RESEARCH 

C COMPILER $219 

DR FORTRAN 77 $219 

LATTICE C COMPILER SCall 

MICROSOFT C 

COMPILER $309 

MS BASIC COMPILER $249 

MS FORTRAN $239 

NORTON UTILITIES- 
NEW SCail 

TURBO PASCAL $45 

Project 
Management 

HARVARD PROJECT 

MANAGER $219 

HARVARD TOTAL 

PROJECT MANAGER $299 
MICROSOFT 

PROJECT $159 

SCITOR PROJECT 

5000 W/GRAPHICS $289 

Professional 
Development 

MANAGEMENT EDGE $159 
SALES EDGE $159 

THINK TANK $119 

Home/Personal 
Finance 

DOLLARS AND 

SENSE $119 

FINANCIER II $119 

HOWARD TAX 

PREPARER 85 $195 

MICROTAX SCail 

MANAGING YOUR 

MONEY $129 



Graphics/Statistics 

ABSTAT $279 

AUTOCAD SCall 
BPS BUSINESS 

GRAPHICS $229 

CHARTMASTER $239 

CHARTSTAR $209 

DR DRAW $199 
ENERGRAPHICSW/ 

PLOTTER $279 

EXECUVISION $259 
GRAPHWRITER 

COMBO $389 

MS CHART $159 
OVERHEAD 

EXPRESS $139 

PC DRAW $259 

PC PAINTBRUSH $ 89 

PFS: GRAPH $ 95 

SIGNMASTER $179 

STATPRO SCall 

STATPAK-NWA $329 

STATPAC-WALONICK $299 

Accounting Modules 

BPI $329 

GREAT PLAINS $479 

IUS EASYBUSINESS $309 

MBA $369 

OPEN SYSTEMS $399 

PEACHTREE $299 

REAL WORLD $469 

STATE OF THE ART $389 
STAR ACCOUNTING 

PARTNER $249 
STAR ACCOUNTING 

PARTNER II $599 

Hardware * 

Multifunction Boards 

AST ADVANTAGE SCall 

AST 6 PAK PLUS (64K) $249 
AST 6 PAK PLUS 

(384K) $449 

AST MEGAPLUS II (64K) $269 

AST MEGAPAK (256 K) $349 

QUADBOARD (64K) $269 

QUADBOARD (256K) $399 
QUADBOARD EXP. 

(64K) $269 
QUADBOARD EXP. 

(384K) $469 

QUAD 512 + (64K) $269 

ORCHID BLOSSOM SCall 

PERSYST SCall 

TECMAR CAPTAIN(64K) $279 

TECMAR WAVE (64K) $209 



Display Boards 

AST MONOGRAPH PLUS SCall 
EVEREX GRAPHICS 

EDGE $419 

HERCULES GRAPHICS 

CARD $329 

HERCULES COLOR 

CARD $179 

PARADISE MODULAR 

GRAPHICS CARD $285 

PARADISE 

MULTIDISPLAY CARD $285 
PERSYST SCall 

PLANTRONICS 

COLORPLUS $419 

PRINCETON SCAN 

DOUBLER SCalf 

STB GRAPHICS 

PLUS II $309 

TECMAR GRAPHICS 

MASTER $489 

TECMAR VIDEO VAN 

GO GH $259 

TSENG ULTRA PAK $449 

Displays 

AMDEK 300G/300A $139/149 

AMDEK 310A $179 

AMOEK COLOR II + $459 

PRINCETON HX-12 $469 

PRINCETON MAX-12 $179 

PRINCETON SR-12 SCall 
QUADRAM 

AMBERCHROME $179 

ZENITH 124 AMBER $145 

ZENITH 135 COLOR SCall 

Modems 

AST REACH 1200 SCall 

HAYES 1200 $459 

HAYES 12008 $399 

HAYES 2400 SCall 
VENTEL 1200 

HALF CARD SCatl 

Accessories 

CURTIS SURGE 

PROTECTORS SCall 
EPD SURGE 

PROTECTORS SCall 

GILTRONIX A/B SWITCH SCail 
MICROBUFFER INLINE 

(64K) $264 
MICROFAZER INLINE 

(64K) $219 

64K RAM SET $40 

256K RAM SET SCall 

8067 MATH $150 



Printers/Plotters 

AMPLOT II $859 

C. ITOH Seal! 

COMWRITER II $CaM 

COMWRITER420 SCall 

DIABLO 620/630 SCall 

EPSON FX-100* SCall 

EPSON LQ-1500 SCall 

EPSON JX-80 SCall 

JUKI 6100 $419 

NEC P3 $899 

NEC 2050 $769 

NEC 3550 $1399 

OKIDATA 84P $729 

OKIDATA 93P $619 

QUME SPRINT 1155 $1569 

TOSHIBA P1351 $1279 
SWEET P 6 PEN 

PLOTTER $899 

Emulation Boards 

ASTPCOX $949 

AST 3780 $609 

AST SNA $689 

AST BSC $ 29 

BLUE LYNX SCall 

CXI 3278/9 SCal! 

IRMA $869 

IRMALINE $999 

IRMAPRINT SCall 

QUAD 3278 $949 

Input Devices 

KEYTRONIC 5151 $189 
MICROSOFT 

MOUSE $139 

PC MOUSE W/ PAINT $159 

Mass Storage 
ALLOY PC-BACKUP 

20MB $1649 
ALLOY PC-DISC 

20MB $1769 

IOMEGA 10 + 10 MB $2895 
MAYNAROWS-1 10MB SCalf 

SIGMA SCall 

SYSGEN IMAGE SCall 
TALLGRASS HARDFILE 

♦ TAPE $C»H 

TEAC HALF HEIGHT $189 

Networks 

AST PC NET SCall 

CORVUS NET SCall 
DIGITAL RESEARCH 

STARLINK $1199 

ORCHID PC NET SCall 

•CALL FOR SHIPPING COSTS 



Samna 
Word III 

'CALL 



Chart-Master 

'239 



AST6Pak 
Plus 

'249 



Quad Board ISmartmodem I Smartmodem 
Expanded64K| 1200B 1200 

'269 '399 '489 




LOWEST PRICE 
GUARANTEE!! 

We will match current 

nationally advertised 

prices on most products. 

Call and compare. 



fie 



p f U 



Diskette 

Library 

Case 

with your order 




TERMS: 

Checks— allow 14 days to clear. Credit processing— add 3%. COD orders— cash, 
M.O or certified check— add $3.00. Shipping and handling UPS surface— add $3.00 
per item (UPS Blue $6.00 per item). NY State Residents— add applicable sales tax. 
All prices subject to change. 



MON.-THURS. 9:00AM-8:00PM 
SUN. & FRI. 9:00AM-4:00PM 



1-S00-221-1260 

In New York State call (718) 438-6057 




Softline Corporation 
P.O. Box 729, Brooklyn, N.Y. 11230 
TELEX: 421047 ATLNUI 



Inquiry 352 



APRIL I985 -BYTE 87 




TARGET 


MARKET 


i 


ESI 


i 


NORTHEAST 


UEST CENTRAL 1 


■V 


i. . 


EAST CENTRAL 



* 



A black border may appear around the Palette slide image, 
which will be imperceptible when projected. 



Now last minute presentations 

can be made from 

your personal computer. 

In color. In house. In minutes. 



Introducing Polaroid Palette. 



Whether your presentation is in 30 
minutes or 30 days, the new Polaroid 
Palette Computer Image Recorder will 
make it easier. Priced at under $1800* it 
lets you make Polaroid instant 35mm 
slides or prints from personal 
computer-generated data. Right at your 
desk. So now you can create a presen- 
tation in minutes. Without sending out 
for processing, paying premiums for 
rush service or risking the security of 
your confidential information. 

Works with the graphics 

packages of the IBM PC or XT, 

DEC Rainbow or PRO, Apple He 

or 11+ and AT&T 6300. 

The Polaroid Palette is designed to 
work with many graphics software 
packages. In fact, when using such 
popular programs as Graphwriter, 
Chart-Master, Sign-Master, DR Draw 
and DR Graph, Palette can virtually 
double both the horizontal and vertical 
resolution of your monitor. Plus, a 

Inquiry 305 



"backfill" feature reduces raster lines 
for a smoother, more finished appear- 
ance. The result— presentation quality 
slides. On-the-spot. 

Color 35mm slides, even from a 
black and white CRT 
Think of it as an artists palette. Be- 
cause Palette "paints" your graphs, 
charts and text. You're choosing from 
up to 72 colors. If you don't want red, 
press a few keys— its green. And if 
you're not the artistic- type, Polaroid 
has developed a menu of color sets: 
combinations of colors that have been 
specially coordinated to complement 
your presentations. And all of this is 
yours, even if you have a black and 
white monitor. 

Lets you make last minute 

changes or add 

up-to-the-minute information. 

The Polaroid Palette is the fast, con- 
venient, low-cost way to prepare slides 
for your presentation. And perhaps 



even more important, Palette allows 
you to keep confidential information 
confidential. You won't have to send 
your work out to anyone again. 

So why wait until the last minute to 
find out about Polaroid Palette? Call 
this toll-free number or return this 
coupon. Because with Palette you'll 
make your deadlines, in no time. 



For a demonstration, call toll-free, or mail the 
coupon to Polaroid Corp,, E.I. Marketing, Dept. 
604, 5^5 Technology Sq., Cambridge, MA 02139. 

CALL 1-800-225-1618 

D Send information. □ Have representative call. 



Name- 



Company - 
Address — 
City 



.Zip_ 



Telephoned 

PC make and model _ 



= Polaroid 



B-4/85 
•Suggested list price. Polaroid* 

APRIL 1985 -BYTE 89 



EVENT QUEUE 



pean Conference on Inte- 
grated Optics, Berlin, 
Federal Republic of Ger- 
many. More than 2 50 engi- 
neers and scientists from 
Europe, Japan, and the 
United States will discuss 
the potential of optics for 
communication, signal pro- 
cessing, and instrumenta- 
tion. Contact ECIO '85 Con- 
ference Secretariat, Frau I. 
Weber-Zuckarelli, Heinrich- 
Hertz-Institut Berlin GmbH, 
Einsteinufer 37, D-1000 
Berlin 10, Federal Republic 
of Germany. May 6-8 

• SPRING COMDEX 

COMDEX Spring, Atlanta, 
GA. More than 750 com- 
panies will exhibit. Contact 
The Interface Group Inc., 
300 First Ave, Needham, 
MA 02194, (800) 325-3330; 
in Massachusetts, (617) 
449-6600. May 6-9 

• MAPLE LEAF 
COMPUTING-The 1985 
Canadian High Technology 
Show, Civic Centre, Ottawa, 
Ontario, Canada. Product 
displays, speakers, and 
tutorials. Contact Canadian 
High Technology Show, Suite 
214, 2487 Kaladar Ave., 
Ottawa, Ontario K1V 8B9, 
Canada, (613) 731-9850. 
May 7-8 

• MEMORY CARDS 
STUDIED-Memory-Card 
Technology, Crowne Plaza, 
San Francisco, CA. See April 
10-11 for details. May 8-9 

• PC DISPLAYS 

PC Expo, Convention Centre, 
Montreal Quebec, Canada. 
Contact PC Expo, 20 But- 
terick Rd., Toronto, Ontario 
M8W 3Z8, Canada, (416) 
252-7791. May 8-10 

• TOPICS IN COMPUTER 

LAW— The Sixth Annual 
Computer Law Institute, Los 
Angeles, CA. Topics on the 
docket include proprietary 
rights issues in the design of 
compatible products, prod- 
uct distribution, and anti- 



trust and copyright issues. 
Contact Cheryl Litrenta, 
University of Southern 
California Law Center, Uni- 
versity Park, Los Angles, 
CA 90007, (213) 743-2582. 
May 9-10 

• C CONVOCATION 

C85: The First International 
Conference on the C Pro- 
gramming Language. 
Ramada Renaissance Hotel, 
San Francisco, CA. A forum 
for programmers and devel- 
opers using or considering 
the use of the C language. 
Sessions on ANSI X3J11 
standard, portability, pro- 
gramming tools, and applica- 
tions. Contact Lifeboat 
Associates, 1651 Third Ave., 
New York, NY 10128, (800) 
847-7078; in New York, (212) 
860-0300. May 13-15 

• GRAPHICS FOR 
ENGINEERING, DRAFTING 

Computer Graphics for 
Engineering/Drafting Practice 
and Computer Graphics 
Workshop, University of 
Texas, Austin. These short 
courses stress learning the 
principles of computer 
graphics and seek to 
develop the ability to 
prescribe computer graphics 
equipment for engineering 
applications. Contact College 
of Engineering, University of 
Texas, Austin, TX 78712, 
(512) 471-3506. May 13-17 

• PROFESSIONAL 

TUTORIALS-Tutorials for 
Professional Development, 
Hyatt Hotel, Los Angeles, 
CA. A series of all-day 
seminars on software, logic 
programming, and communi- 
cations. Contact Gerry Segal, 
Association for Computing 
Machinery, 11 West 42nd St., 
New York, NY 10036, (212) 
869-7440. May 13-17 

• TEST MEASUREMENT 

EXPO-The 1985 Test and 
Measurement World Expo, 
Convention Center, San lose, 
CA. Conferences and tech- 
nology exhibits. Contact 



Meg Bowen, Test and 
Measurement World Expo, 
215 Brighton Ave., Boston, 
MA 02134, (617) 254-1445, 
May 14-16 

• MODULA-2 ENGI- 
NEERING— Software Engi- 
neering with Modula-2, 
Atlanta, GA. A course em- 
phasizing methods for 
building large-scale software 
systems in Modula-2. Prereq- 
uisite: knowledge of Ada or 
Pascal. The fee is $495. 
Contact Elaine Hadden 
Nicholas, Department of 
Continuing Education, 
Georgia Institute of Tech- 
nology, Atlanta, GA 
30332-0385, (404) 894-2547. 
May 15-17 

• OK SHOW 

The Eighth Annual Show & 
Tell Microcomputer Con- 
ference, University of 
Oklahoma, Norman. Micro- 
computer fans of all ages 
and levels of expertise come 
together to share ideas and 
demonstrate applications 
and hardware. Contact 
Richard V. Andree, Show & 
Tell Computer Conference, 
Mathematics Department, 
University of Oklahoma, 601 
Elm St, Norman, OK 73019. 
May 18 

• MANAGEMENT 
CONGRESS-Update '85, 
Sheraton Hotel, Brussels, 
Belgium. A briefing covering 
technological developments 
for those in the information 
management and micro- 
graphic industries. Contact 
Update '85, International In- 
formation Management Con- 
gress, POB 34404, Bethesda, 
MD 20817, (301) 983-0604. 
May 20-22 

• CAD TECHNOLOGY 

CAD 2001: The Countdown, 
Dallas, TX. Presentations on 
the future of computer-aided 
design. The fee is $900. 
Contact CAD Seminars Inc., 
Suite 400, 1 50 East River- 
side, Austin, TX 78704, (512) 
445-7342. May 22-24 



• SOFTWARE AND 
HUMAN DEVELOPMENT 

Computer Software and 
Human Development Con- 
ference, Royal York Hotel, 
Toronto, Ontario, Canada. 
Held in conjunction with the 
Third Annual Software 
Panorama, this conference 
will examine the impact of 
software development on 
business, education, health, 
and agriculture. Contact 
Reuben Lando, The Software 
Developers Association, 
Suite 500, 185 Bloor St. E, 
Toronto, Ontario M4W 1C8, 
Canada, (416) 922-1153. 
May 22-24 

• DISK STORAGE EXPO 

The 1985 International 
Videodisc, Optical Disk, and 
CD-ROM Conference and 
Exposition, London West 
Hotel, London, England. 
Workshops, presentations, 
and exhibitions, Contact 
Angela Suter, Meckler Com- 
munications, 11 Ferry Lane 
W, Westport, CT 06880, 
(203) 226-6967; in England, 
Alice Taylor, Meckler Com- 
munications, c/o Eurospan, 3 
Henrietta St., London WC2E 
8LU England; tel: 01 
240-0856. May 29-31 

• MANAGE PROGRAMS 

Configuration Management 
of Software Programs, 
Washington, DC Methods 
for controlling the costs of 
development, maintenance, 
and operation of software 
Contact Stod Cortelyou, 
Continuing Engineering 
Education, George Washing- 
ton University, Washington, 
DC 20052, (800) 424-9773; 
in the District of Columbia, 
(202) 676-8520. May 29-31 

• COMPUTER INTER- 
FACING— Personal Computer 
and STD Computer Interfac- 
ing for Scientific Automa- 
tion, Virginia Polytechnic In- 
stitute and State University, 
Blacksburg. A hands-on 
workshop with participants 
wiring and testing interfaces. 
The fee is $450. Contact Dr. 



90 B YTE • APRIL 1985 



EVENT QUEUE 



Linda Leffel, C.E.C, Virginia 
Polytechnic Institute and 
State University, Blacksburg, 
VA 24061, (703) 961-4848. 
May 30-]une I 



June 1985 

• LEARN TO BUILD 
PROGRAMS-First North 
American Summer School 
on Program Construction, 
Newport, RI. Methods for 
the effective construction of 
software will be taught. Con- 
tact Teleprocessing Inc.. 60 
State St., Boston, MA 02109, 
(617) 367-6227. ]une 3-12 

• INTERFACES FOR 
SCHOOL LABS-lnterfacing 
for School Laboratories, 
Miami University Oxford, 
OH. A workshop for sec- 
ondary-school and college 
teachers on the construction 
and use of interfaces for 
laboratory instrumentation. 
Contact Bill Rouse, 301 
McGuffey Hall, Miami 
University, Oxford, OH 
45056, (513) 529-2141. 

)une 3-14 

• COMPUTER 

MAINTENANCE 
Independent Computer 
Maintenance, Halloran 
House New York, NY. Con- 
tact Carol Every, Frost & 
Sullivan Inc., 106 Fulton St.. 
New York, NY 10038, (212) 
233-1080. \um 5-6 

• OPTICAL-STORAGE 

CONFERENCE-First Annual 
Conference on Optical 
Storage for Small Systems, 
Biltmore Hotel, Los Angeles, 
CA. Contact Technology Op- 
portunity Conference, POB 
14817, San Francisco CA 
94114-0817, (415) 626-1133. 
}une 5-7 

• COMPUTERS FOR SALE 

Computer Supermarket, San 
Mateo County Fairgrounds, 
San Mateo. CA. Retailers, 
manufacturers, and dis- 
tributors will be selling hard- 



ware and software. Admis- 
sion is $7; children $3. Con- 
tact Microshows, Suite 203, 
1209 Donnelly Ave., Bur- 
lingame, CA 94010, (415) 
340-9113. June 8-9 

• COMPUTER VISION 
CONFERENCE-Computer 

Vision and Pattern Recogni- 
tion Conference, Cathedral 
Hill Hotel, San Francisco, 
CA. Submitted and invited 
technical papers. Contact 
Computer Vision and Pat- 
tern Recognition, POB 639, 
Silver Spring, MD 20901, 
(301) 589-8142. }une 9-13 

• MUMPS MEETING 
The Fourteenth Annual 
Meeting of the MUMPS 

Users' Group, McCormick 
Center Hotel, Chicago, IL. 
Tutorials, workshops, site 
visits, discussions, and ex- 
hibits. Contact MUMPS 
Users' Group, Suite 510, 
4321 Hartwick Rd., College 
Park, MD 20740, (301) 
779-6555. ]une 10-14 

• ROBOTIC STRATEGIES 
Robot Manipulators, Com- 
puter Vision, and Intelligent 
Robot Systems, University of 
Stirling, Stirling. Scotland. A 
short course for profes- 
sionals emphasizing the 
development of strategies 
for the solution of robotic- 
sensing, spatial-reasoning, 
and manipulation problems. 
Contact Director of the Sum- 
mer Session, Massachusetts 
Institute of Technology, 
Room E19-3 56, Cambridge, 
MA 02139. [urn 10-14 

• NETWORK CONTROL 

AND MANAGEMENT-Net- 
work Management/Technical 
Control, Santa Clara Mar- 
riott, Santa Clara, CA. See 
April 18-19 for details. 
Jum 12-13 

• CLINICAL COMPUTING 

Computing in Clinical 
Laboratories: The Fifth Inter- 
national Conference, Stutt- 
gart, Federal Republic of 

[continued) 




PT'tt 



TM 



DISCOVER muLISP 

The Artificial Intelligence 
Package for Micros. 

muLISP includes: 

■ An integrated environment for A.I. program 
development. 

■ A high performance, pseudo-code compiler 
and interpreter for the LISP programming 
language. 

■ A resident, screen-oriented LISPeditorand 
debugging system. 

Available for your IBM PC™, MS-DOS™, 
CP/M™, and Apple™ II SoftCard computers. 

We also offer muMATH™, the symbolic math 
calculator for micros. 



Founded 1979 



1771 Aft 

s==! Worehou/e 

P.O. Box 11174, Honolulu, HI 96828-0174- (808) 734-5801 (AfterNoon PST) 
MC/VISA MCI ID: 241-7437 c 1985 Soft Warehouse 



■ I'd like to know more about muLISP 
and muMATH. Please send me more 
m information today. 



Name 

Address . 
City 



State. 



Zip- 



Company. 
Position 



I j 



APRIL 1985 'BYTE 91 




100% FLAWLESS 
COPIES . . . 

. . . FAST! 



No need to tie up your valuable computer to duplicate 
diskettes , . . when VICTORY can provide you with a 
duplicator that will do the job flawlessly, and much 
faster. One button operation automatically formats, 
duplicates and verifies up to 8 diskette copies at the 
same time. 

VICTORY can supply you with literally dozens of 
standardized formats to match the protocol of virtually 
any current computer. In addi- 
tion, built-in utilities enable 
you to read or devise any for- 
mat you may require. If that's 
not enough, VICTORY can 
help you with unusual or 
unique formatting, serializing 
or copy-protecting problems. 

VICTORY duplicators are 
designed to be reliable. Each 
of the copy drives has a 
separate controller to increase 
copying throughput and 
ensure maximum uptime. 
VICTORY Duplicators use 
industry proven drives com- 
bined with 100% digital tech- 
nology . . . there are no 
analog circuits to slowly drift 
out of tolerance. 

Let us help free you from 
your disk-duplicating bottle- 
neck at a surprisingly 
attractive price. Write or call: 
VICTORY ENTERPRISES 
TECHNOLOGY, INC., 8910 
Research Blvd., Suite B2, 
Austin, Texas 78758— 
(512)450-0801. 







\M7 VICTORY 

\j7 ENTERPRISES 

^f Technology, Inc. 



EVENT QUEUE 



Germany. Topics on the 
agenda include databases, 
data presentation, and ex- 
pected developments. Dem- 
onstrations and exhibits. 
Contact PD Dr. Chr. 
Trendelenburg, Katharinen- 
hospital KG, Kriegsberg- 
strasse 60, D-7000 Stuttgart 
1, Federal Republic of Ger- 
many; tel: (07 11) 20 34-4 
82. lune 12-14 

• COMPUTERS IN 

CLINICAL LABS-Clinical 
Laboratory Computers, Sym- 
posium 1985, The Towsley 
Center, University of 
Michigan, Ann Arbor. Con- 
tact Dove Margenau, Office 
of Continuing Medical 
Education, The Towsley 
Center, Box 057, The Univer- 
sity of Michigan Medical 
School, Ann Arbor, MI 
48109-0010, (313) 763-1400. 
lune 12-14 

• INFO MANAGEMENT 
EXPO, CONFERENCE 

Info/West: The Western Infor- 
mation Management Exposi- 
tion and Conference, Con- 
vention Center. Anaheim, 
CA. Trade show for ex- 
ecutives and data-processing 
and management-informa- 
tion system managers. Con- 
tact Info/West, 999 Summer 
St., Stamford, CT 06905, 
1203) 964-8287. lune 12-14 

• FORTH CONFERENCE 
The 1985 Rochester FORTH 
Conference, University of 
Rochester, Rochester, NY. 
The focus will be on soft- 
ware engineering and man- 
agement. Contact Ms. Maria 
Gress, Institute for Applied 
FORTH Research, 70 
Elmwood Ave., Rochester, 
NY 14611, (716) 235-0168, 
lune 12-15 

• LOGICAL MACHINES 
CONFERENCE-The Second 
Annual Conference on Logic. 

Logic Machines, and Public 
Education, University of 
Houston-Clear Lake, Hous- 
ton, TX. Formal and infor- 
mal sessions, symposia, and 



workshops. Contact the 
Institute for Logic and 
Cognitive Studies, Univer- 
sity of Houston-Clear Lake, 
Box 269, Houston, TX 
77058, (713) 488-9274. 
\une 13-15 

• INTERNATIONAL SHOW 

The International Computer 

Show, Trade Fair Center, Col- 
ogne, West Germany, More 
than 3 50 manufacturers 
from more than 18 countries 
are expected to display their 
wares. Contact Messe- und 
Ausstellungs-Ges.m.b.H. 
Koln, Messeplatz, Postfach 
210760, D-5000 Koln 21, 
West Germany; tel: (0221) 
821-1; Telex: 8 873426 mua 
d. lune 13-16 

• PC IN BIG APPLE 

PC Expo, Coliseum, New 
York, NY. Seminars and 
product displays. Contact PC 
Expo, 333 Sylvan Ave., 
Englewood Cliffs, NJ 07632, 
(800) 922-0324; in New 
Jersey, (201) 569-8542. 
lune 17-19 

• SOFTWARE FOR ENGI- 
NEERING— Engineering Soft- 
ware: Engsoft 85, The 
Fourth International Con- 
ference and Exhibition, Ken- 
sington Exhibition Centre, 
London, England. Exhibits 
and sessions of software for 
engineering. Contact Eiaine 
Taylor, Computational 
Mechanics Centre. Ashurst 
Lodge, Ashurst, Southamp- 
ton S04 2AA, England; tel: 
(042 129) 3223; Telex: 
47388 Attn. COMPMECH. 
lune 18-20 

• GRAPHICS IN SUNSHINE 

Computer Graphics '85 
West, Los Angles, CA. Con- 
tact National Computer 
Graphics Association, 8401 
Arlington Blvd., Fairfax, VA 
22031, (703) 698-9600. 
lune 2 5-27 

• CAD TECHNOLOGY 

CAD 2001: The Countdown, 
Boston, MA. See May 22-24 
for details, lune 26-28 ■ 



92 BYTE* APRIL 1985 



Inquiry 396 



Our multi-mode HERMES printers shake hands 
with all kinds of computers. Even some you've 




And for your IBM-PC™, 

we have created the fully 
compatible multi-mode 
HERMES PC-PRINTER 1 



Fully compatible with your IBM-PC™, tested with 
Easy writer™, Multiplan™, Lotus 1-2-3™ and other soft- 
ware packages, the HERMES PC-PRINTER 1 allows you 
to convert your personal computer to a heavy duty pro- 
fessional system. IBM-PC™ users who only pick the best 
will also appreciate : 

Its speed. Bi-directional, shortest path printing. 200 cps 
Data, 100 cps Near Letter Quality (single pass). 

Its resolution. Finest print quality available on a matrix 
printer. So good you can even print signatures. Bit 
mapping graphics in single, double and triple density 
modes. 

Its quality. Swiss high quality construction. Very high 
reliability for heavy duty use. 

Its versatility. Choice of printing styles with the 
complete IBM™ character set tables (226 chars.). Wide 
range of automatic sheet-feeders with 1 or 2 bins + 
envelopes, single document inserter, roll-holder and 
tractor. 

Its ease of use. Plug'n play installation. Plug it in, switch it 
on yourself. 

HERMES* 

The impressive printers 

Manufactured in Switzerland by HERMES PRECISA INTERNATIONAL, 
CH-1401Yverdon. 

HERMES printers are distributed in Australia, Austria, Canada, Cyprus, Finland, 
France, Greece, Hong-Kong, Indonesia, Jordan, Kuwait, Lebanon, Macao, Malaysia, 
New-Zealand, Philippines, Saudi Arabia, Singapore, South Africa, South Korea, 
Spain, Sweden, Switzerland, Taiwan, Thailand, United Kingdom, USA, West 
Germany. 

Contact factory direct for OEM sales of print-heads and printer mechanisms. 





To receive a sample of the finest quality matrix print-out 
and additional information on the HERMES PC-PRINTER 1, 
please return the coupon below. 



| Please send me more documentation about your PC-PRINTER 1 




Name^ 



Title 



Company 


Street 




City 




State 


Zip 


Phone ( 


) 



Send to: HERMES PRODUCTS, Inc. - Printer Division 

1900 Lower Road, LINDEN, NJ 07036, (201) 574 0300 



Inquiry 185 



APRIL 1985 -BYTE 93 



Three more firsts 
from the people who 
invented the wheel. 






XEROX 



From day one, Xerox and Diablo 
have been known as the two best 
names in daisywheel printers. And 
now there are three more in the 
Xerox line to choose from. 

The Xerox Advantage D-25 
Diablo printer turns out letter qual- 
ity documents quickly and quietly. 
And it does all that for the price of 
a dot matrix printer. 

A^ < — ^At80 




c.p.s., the D-80IF is the fastest 
daisywheel printer ever made by 
Xerox. It has a built-in double bin 
sheet feeder. As well as 
the capacity to handle up 
to 16 computers at once. 

And the D-36 spells 
reliability. It averages 4,000 hours of 
printing between maintenance calls. 

But Xerox didn't stop there. 
Each of these new machines is 
compatible with most computers 
on the market, including the 
IBM-PC. And they're 
Jfo all easy to use. 




N, 



** 



They're also a part of Team Xerox, 
so they can be serviced by the 
national Xerox service force and 

authorized service loca- 
tions across the country. 

So if you're looking 
for the latest in daisy- 
wheel printing technology, go with 
the people who've been in the busi- 
ness the longest. Call 1-800-833-2323, 
exL 25, your local Xerox office, an 
authorized Diablo or Xerox dealer 
or send your business card to Xerox 
Corporation, DepL 25192, PO. 
Box 24; Rochester, NY 14692. 

For more information from Xerox, 
circle 405 on the Reader Service card. 



i 



./-■ 



XKROXw. Diablo" and the identifying 
IBM ' is a registered trademark of Inle 



of XEROX CORPORATION. 






WHAT'S NOT 



Knife the Mac 



Ennui Associates has an- 
nounced MacKnifer, a 
hardware attachment that 
mounts on the side of your 
Macintosh and sharpens 
knives, scissors, lawn-mower 
blades— anything in your 
home that needs sharpen- 
ing. With MacKnifer's 
patented double-action 
grinding wheel, you can 
easily sharpen any utensil in 
less time than it takes the 
Mac to open a file. Accord- 
ing to the manufacturer, 
MacKnifer is so easy to use 
that you can operate it 
within 30 minutes of taking 
it out of the box, Turn your 
spare computing time into 



Nouveau-Chic Luggage 




extra cash with a knife- 
sharpening business on the 
side ... of your Macintosh. 

For more information on 



MacKnifer, contact Ennui 
Associates, 52 502 Marginal 
Ave., Somnolencia, CA 
90541. 



The Spike Untermeyer 
Luggage Company man- 
ufactures hollow replicas of 
the most popular lap-size 
and transportable personal 
computers for use as travel 



bags by status-conscious 
travelers. For example, the 
Untermeyer Executive Port- 
folio resembles a Tandy 
Model 100, complete with 
movable (nonfunctional) 




keys. The Executive Portfolio 
flips open to reveal enough 
space for a pad, appoint- 
ment calendar, several pens 
and pencils, or a couple of 
peanut butter and jelly 
sandwiches for that quick 
executive snack. The 
Untermeyer Overnighter, 
easily confused with a Com- 
paq, TI, or IBM portable 
computer, is perfect for that 
sudden business trip, 

Untermeyer luggage is 
painfully authentic. The 
Overnighter is exactly half 
an inch too large to fit 
under the average coach 
airline seat, and the bottom 
of the case is heavily 
weighted to ensure that nas- 
ty crack on the shins when 
you maneuver past the flight 
attendant. 

For more information, con- 
tact the Spike Untermeyer 
Luggage Company Inc.. 442 
Glenwood Ave., Prosaic, NJ 
22104, 



One for the Road 

Honda Corporation has 
announced the Trans- 
porter, the first truly trans- 
portable computer. With a 
few simple twists, you can 
transform the Transporter 
from a portable computer 
(with full keyboard, 24-line 
by 80-column display and 
two microfloppy-disk drives) 
into a single-passenger auto- 
mobile. 

The Transporter runs on 
32 D-cell batteries (not in- 
cluded) with additional one- 
year battery backup for the 
ignition, which is in ROM 
(ride-only memory). Thus, if 
the Transporter won't start 
on a chilly winter morning, 
you can simply give it a 
cold boot to jog its memory. 

Although the Transporter 
is somewhat heavier than 
other portable computers, 
you can easily drive it 
through airport terminals. 
Service will be available 
through AAA (American 
ASCII Association), which 
provides pickup and 
delivery with no tote- 
charges. 

Options include the TP-100 
Printer Trailer, the 300- 
BeePS Modem, and a gen- 
uine Naugahyde keyboard 
cover. Honda has also an- 
nounced plans to release 
the SemiPortable, a 20- 
megabyte hard-disk system 
that transforms into an 
18-wheeI tractor/trailer 
(assembly required). 

The Transporter is 100 per- 
cent compatible with the 
popular Toyota Corolla and 
runs on most operating 
roads. The cost is $5995. 
For more information, con- 
tact Honda Corporation Ltd., 
2 Duryea Drive, Minikin, MI 
48101. 



96 BYTE 



APRIL 1985 



New Arrival 



Home on the Database 



Celebrity Software, maker 
of the Howard Cosell 
Word Processor and the 
Michael Jackson Spread- 
sheet, has announced the 
Princess Di Database. If your 
data is a royal mess, this 
hierarchical database will ar- 
range things in a neat suc- 
cession for you. You can ob- 
tain output from the system 
every nine months, with 
three levels of security: 
Mum's the Word, Rumor 
City, and Tell the World. 

Available at supermarket 
checkout counters, the 
Princess Di Database is 
priced at $49.95 from 
Celebrity Software, 1 3 5 
Pachelbel Canyon, San 
Regales, CA 90342. 



New Mag 



High Press Technologies 
(HirJIech) has an- 
nounced a new publication, 
Personal Photocopying. Designed 
to make photocopiers less 
threatening for the average 
person, the magazine will be 
written in nontechnical lan- 
guage that explains PRINT 
PAUSE, and CANCEL in 
language that a layperson 
can understand. 

Articles in the first issue of 
PPC will include "1001 Ways 
to Make Money with Your 
Photocopier," "Paper Jam- 
Deadly Threat to Your Busi- 
ness," and "Big Gray: The 
Xerox Story." 

Based on research done in 
its own offices. HipfTech has 
also announced Constant 
Coffeemaking. For a one-year 
subscription to either 
magazine, send $2 5 to POB 
123123, South Banausic, WI 
03458. 



ThinkFast Software has 
introduced a revolution- 
ary natural-language data- 
base designed for home 
management. MOM, the 
Model Management pro- 
gram, is a matriarchal 
database of home-related 
subjects that responds to 
plain-English queries. After 
entering information about 
your home, age, eating 
habits, and shoe size, you 
enter search phrases in the 

A Taste of Security 



format "Where is the 
screwdriver?" After a quick 
pass through its files, MOM 
responds, "Right where you 
left it-behind the TV set." 
Enter the search phrase, 
"Where are my sneakers?" 
and MOM responds with 
lightning speed, "I don't 
know where your sneakers 
are; I don't wear your 
sneakers." 

ThinkFast has also an- 
nounced a product for in- 




If merely erasing sensitive 
data is not enough for 
you, Soycure Systems of 
Tokyo has developed the 
ultimate in disk security. 
Made entirely of processed 
soybeans, Para soya Disks 
are writable, readable, and 
edible. Parasoya disks con- 
tain 84 percent more pro- 



tein than average floppy 
disks and are available in 
5 ^-inch (regular) and 
3 /2-inch (crunchy) formats. 

Available at computer and 
health stores everywhere, 
Parasoya Disks are priced at 
$50 per 10-pack from Soy- 
cure Systems, 1 Tufchuying, 
Tokyo, Japan. 



tegration with MOM, one 
that provides personal ad- 
vice and guidance. Decisions 
and Declarations (DAD) 
responds to the traumas of 
everyday living with such 
plain-English messages as, 
"You want to cry? I'll give 
you something to cry 
about!" and "Ask MOM." 

MOM and DAD are priced 
at $99 each from ThinkFast 
Software, Duitmy Way, 
Homeville, NC 28210. 

Keeping Time 
to Yourself 

Incognito, a low-profile 
time-management pro- 
gram for MS-DOS com- 
puters, combines an ap- 
pointment calendar with 
200 stock excuses for break- 
ing or avoiding social 
engagements. 

The Incognito calendar's 
avoidance categories in- 
clude: My Mate and I; The 
Car; Kids. Pets, and Rela- 
tives; Let Me Check With 
My . . . (accountant, boss, 
etc.); I'm Coming Down With 
. . . ; and Previous 
Engagement. 

Incognito's Fib-jogger utili- 
ty reminds you what you 
said to whom and tells you 
when you've ducked some- 
one more than a set 
number of times. The pro- 
gram also generates fake 
itineraries, resumes, and 
credit references. 

For your copy of In- 
cognito, send $395 to 
ApresHeures Computing, 70 
Main St., Paulsboro, NH 
03458, (800) 123-4567. Call 
after 6 p.m. Please allow 10, 
maybe 12 weeks for 
delivery 



APRIL 1985 'BYTE 97 



Texas Instruments announces 
Dn L*S* Montejo Professional 





7 



'$W®R&: 



u 



Dr. L.N. Montejo* 

{ \irdiac Anesthesiologist, 

Mosfmi, Massachusetts. 



!S52i*F''- 



rfc.w 



fc->v 



the 

Computing System* 



No two individuals work alike* TI had 
unique answers to help Dr* L* S* Montejo 
keep his patients and his business healthy* 



U I used to walk out of the operating 
room with a clipboard and a chart " 
says Dr. L S. Montejo. "Now I walk 
out with a floppy disk." 

Dr. Montejo is a prominent anes- 
thesiologist who is pioneering the 
use of personal computers in heart 
surgery. His unique idea for making 
quicker, more informed decisions 
led to a unique solution from TI: a 
portable PC he could talk to. Con- 
figured to his exact needs from the 
wide range of TI options. 

"Using TIs Speech Command ," 
he says, "I can respond to drug 
reactions faster, with the PC mak- 
ing calculations as I speak to it. And 
my hands are free to do other things. 

"The information just flies by* 

But the computer organizes it, and 
by calling up color charts, I can 
make better decisions at a glance. It 
lets me provide better medical care." 

In his office, Dr. Montejo uses a 
desktop TI Professional Computer 
to keep the business side of his 
practice operating smoothly. 
"Having to wait on a computer is 
a waste of valuable time " he says. 
"TI runs software fast. And the TI 
screen has a lot better resolution 
than other monitors." 



His TI 855 printer also speeds up 
the paperwork. "We can use it to go 
from draft to letter quality imme- 
diately, and change typefaces very 
quickly by using the control panel 
instead of software commands." 

TI had what the doctor ordered 
to put together a complete PC sys- 
tem for his specific needs. Including 
a solution for a budding computer 
genius in his family. "My daughter" 
he says, "loves her Speak & Spell." 

TI has the right answers 
for the way you work* 

With TIs broad line of versatile 
computer products, you can put 
together a system unique enough 
to put your own name on it. Your 
TI dealer can provide you with 
just the right combination of 
hardware, software, service and 
support for your special needs. For 
more information and the location 
of your nearest TI dealer, call 
1-800-527-3500. 

Texas 
Instruments 

Creating useful products 
and services for you. 




From desktop, portable and briefcase PCs to minicomputers and a full line of printers, 
you can assemble a TI system as unique as you are. 



2775-06 
© 1985 TI 



APRIL 1985 'BYTE 99 



W*HftgW 



(££ 



BYTE 



Features 



Ciarcias Circuit Cellar: 
Build the Home Run 
Control System, 
Part I: Introduction 

by Steve Garcia 102 

Coprocessing in Modula-2 

by Colleen Roe Wilson 113 

A Million-Point Graphics Tablet 

by lames Hawley 120 



IN JANUARY WE PRESENTED a real feast in the Features department; because 
we had no theme section, we were able to publish 1 1 articles on a wide vari- 
ety of topics. This month, the significance of our theme on artificial intelligence 
and the depth of coverage it required limited the space we had available for 
features. Next month we'll return with our usual number. 

As we hinted in the March Features introduction, this month Steve Ciarcia 
begins a three-part project that he's wanted to build for some time. The Circuit 
Cellar Home Run Control System takes up where Steve's first project of this 
type left off some years ago (see "Build a Touch Tone Decoder for Remote 
Control," December 1981, page 42). Imagine full programmable control over 
just about any outlet in your home. Lights can turn on and off automatically 
as you enter and leave a room. You can design a complex surveillance and 
security system that includes automatic emergency dialing. And you can phone 
home, check system status, and make modifications to the control system to 
suit your schedule. All in all, Steve was pretty happy with his original 1981 
design, but with recent technological advances and his eye for improvement, 
he developed the Home Run Control System to be a lot friendlier and deliver 
a lot more. 

In August 1984 the BYTE theme was Modula-2. Heralded by many as the 
language of the future, it also has detractors, some of whom point out that 
Modula-2 is only an upgrade of its Pascal ancestor with problems of its own. 
Colleen Roe Wilson's "Coprocessing in Modula-2" describes Modula-2 's facility 
for the development of concurrent programs, one of its significant differences 
with Pascal. 

If you have a Zenith Z-100 and are interested in exploiting its graphics 
capabilities, you might want to build "A Million-Point Graphics Tablet" based 
on Koala Technologies' KoalaPad. James Hawley shows you how to add the 
appropriate components and interface it to the Z-100's S-100 bus. With his 
graphics tablet, you can use a stylus instead of a light pen for pinpoint con- 
trol over your drawings. 

— Gene Srnarte. Managing Editor 



APRIL 1985 'BYTE 101 




COPYRIGHT © 1985 STEVEN A ClARCIA. ALL RIGHTS RESERVED 




CIRCUIT CELLAR 



BUILD THE 

HOME RUN CONTROL 

SYSTEM 

PART 1: INTRODUCTION 

by Steve Ciarcia 




Energy management, convenience, 
and security in one package 



Six years ago I presented an article on building a computer- 
controlled security system using an SDK-85 experimenters 
board. To this day, I still get letters asking for software and 
material sources. Since home/industrial energy and security 
management have been and still are a major interest (and 
little has been published since then), that article remains a 
popular reference for students and experimenters. 
As I look back on it now, I realize that my first home-control computer was 
engineered properly but was about as user-friendly as ENIAC. It's time to re- 
address the subject, bring the design up to date, and make this home-control 
system a real friend. 

1 conceive of this project as a simple computer control system equally ap- 
plicable in the home or factory. The choice of input sensors and output con- 
trols designates its primary application. 

Whether for industrial or home use control systems function similarly 
Specific input data is analyzed and compared to a predetermined set of ac- 
tion parameters. If a favorable comparison exists, the designated task is per- 
formed. For example, if a light is to be turned on at 2:00 p.m., the control 
system sees a negative request-affirmation comparison until that time. At that 
instant, the output of the control system turns on the light and then continues 
with the next request. In a control system configured as an alarm, the inputs 
would be from contact closures, and the outputs would be to bells, automatic 
dialers, and other such items. 

Whatever the application, control systems are designed to be either open 
loop or closed loop in function. An open-loop controller simply outputs its 
decision and forgets about it. Industrial control systems, on the other hand, 
require more assurance that the action has been performed. They close the 
loop by analyzing feedback signals from the operation being controlled. If 

{continued) 

Steve Ciarcia (pronounced "see-ARE~see-ah") is an electronics engineer and computer 

consultant with experience in process control digital design, nuclear instrumentation, and 

product development. He is the author of several books about electronics. You can write to 

him at POB 582, Glastonbury, CT 06033. 



PHOTOGRAPHED BY PAUL AVIS. STYLED BY JANE SUTTON 



APRIL 1985 • BYTE 



103 



CIRCUIT CELLAR 



a heating element is turned on, a cur- 
rent sensor in series with the ele- 
ment's power source or a temperature 
sensor next to the element indicates 
positively that the action has been 
performed. 

It is this open-loop versus closed- 
loop configuration that, for most ap- 
plications, defines whether a con- 
troller is consumer or industrial quali- 
ty. I beg to differ with the trend, 
however, and feel that it is about time 
a system successfully bridged the gap 
The Circuit Cellar Home Run Control 
System (HCS) is the result. 

My intention is not to directly ad- 
dress the industrial market with my 
HCS. Rather, I will apply some of my 
industrial process-control experience 
to produce a design that offers flex- 
ibility and reliability as a home-control 
and energy-management system. If 
you are in the process-control busi- 



ness, you will soon realize that its 
sophistication and cost-effectiveness 
make it ideal for dedicated industrial- 
control applications where you might 
ordinarily use an expensive program- 
mable controller. 

Home Run Control System 

Practically all commercial home- 
control systems use BSR X-10 remote- 
control power modules. They are sold 
under a variety of trademarks: Plug- 
N-Power, Sears Home Control, BSR 
X-10, and GE HomeMinder. These 
remotely controlled power switches 
turn the power on or off to lights and 
appliances that are plugged into 
them. A separate controller activates 
the individual switches by transmitting 
a coded command sequence through 
the power lines. Command controllers 
are available that perform timed or 
telephone-designated activations. 



The Plug-N-Power or Sears Home 
Control system is quite adequate for 
most open-loop applications. An at- 
tic fan that needs to run two hours a 
day to keep the attic cool could use 
a timer-activated BSR module. Simply 
set the command unit to turn the fan 
on from 1:00 to 3:00 every afternoon, 
for example. Of course, on really hot 
days the attic fan will need to run 
longer, and on rainy days you'll be 
wasting power. If you compensate 
(close the loop) by changing the run 
time each day, it is hardly a home- 
control system. Instead, it is merely a 
more convenient manual power 
switch. 

The solution is to use a true closed- 
loop control. By adding a 120- to 
135-degree thermostatic switch in the 
attic, the control system can know 
when the attic is hot and has to be 
exhausted. A 90-degree thermostatic 



6802 

MICROPROCESSOR 



16K BYTES 
RAM 



n 




TERMINAL MODEM 



J I 



SERIAL 
I/O 



u 



7*s 



7Y 



24K BYTES 
PROGRAM ROM 



KEYBOARD 
ENCODER 



<^> 



24-LINE BY 40- 
CHARACTER 
VIDEO -DISPLAY 
GENERATOR 



PARALLEL ENCODED OR 
SCANNED MATRIX KEYBOARD 



11 5 VAC 




POWER 
SUPPLY 




BATTERY 

BACKUP 


LINE 


i 












BSR 
TRANSMITTER 











COMPOSITE 

VIDEO TO 
MONITOR 



RF 

VIDEO TO TV 



Figure 1: A block diagram of the Circuit Cellar Home Run Control System. 



104 BYTE* APRIL 1985 



CIRCUIT CELLAR 



switch is also wired in. When the at- 
tic temperature reaches 135 degrees, 
the fan turns on. It turns off when it 
gets to 90 degrees. The BSR control 
modules could still provide the on/off 
power to the fan, but the control deci- 
sion is more adequately defined by 
directly monitoring the temperature 
with heat sensors than by simple 
timed activation. This way, the fan will 
stay on as long and often as needed. 
On cloudy or rainy days, the fan might 
not come on at all. (I am aware that 
special thermostatically controlled 
attic-fan switches can accomplish this 
specific task without a computer. 1 am 
not trying to find a specific solution 
but rather to demonstrate the two 
control approaches as they apply to 
general-purpose control systems.) 

The immediate answer to open-loop 
BSR control is to add more intelli- 
gence in the form of a computer. Pres- 
ently, many control systems on the 
market use personal computers. Using 
the parallel I/O (input/output) and 
display capabilities of the personal 
computer with a specialized BSR 
transmitter card installed, many com- 
panies have successfully designed just 
the kind of home-control system I'd 
want. However, such a seemingly 
economical approach uses the entire 
function of the computer. You can 
have a $2 500 Apple II home con- 
troller or suffer when the entire 
system grinds to a halt because 
you've loaded a word-processing pro- 
gram. Besides, it can cost $10 a month 
just to run an IBM PC 24 hours a 
day— and don't forget the cost of the 
uninterruptible power supply. 

Ultimately, successful computer- 
based energy-management and 
home-control systems must have 
completely dedicated functions. Try- 
ing to time-share tasks among games, 
word processing, and environmental 
control is simply more complicated 
than it's worth. The age of specialized 
computers is at hand. 

The Circuit Cellar HCS is designed 
specifically for that task. It is a single- 
board microprocessor-based con- 
troller that uses a combination of 
both open- and closed-loop control 
design. It takes advantage of the cost- 



effective BSR control modules and 
fully duplicates any of the manual, 
automatic, or timed functions present- 
ly supported in the BSR product line. 

The Circuit Cellar HCS closes the 
control loop with 16 hard-wired digital 
input and 8 TTL (transistor-transistor 
logic)-compatible hard-wired output 
lines. Relays, contact closures, motion 
detectors, and thermostatic switches 
can be connected to these I/O lines 
for direct "sense and respond" ac- 
tivities. It can also accommodate 48 
BSR modules. Figure 1 is a block 
diagram of the HCS. 

The 6802-based HCS is a stand- 
alone control unit (see photo 1) com- 
plete with battery backup. Photo 2 
shows the prototype circuit board that 



mounts inside the control unit. The 
HCS communicates with the user 
through either a serial terminal or 
video monitor and keyboard. In the 
terminal mode, RS-232C communica- 
tion is at 75 to 4800 bits per second 
(bps). 

The HCS optionally supports an in- 
tegral video-display generator to pro- 
vide a 24-line by 40-character display 
either directly to a composite video 
monitor or to a television set. A 
keyboard encoder allows connection 
of either an Apple Il-compatible 
parallel-encoded keyboard or an un- 
encoded scanned-matrix keyboard. 
Finally, the HCS can communicate 
with other systems. An additional con- 

{continued) 




Photo 1: Home Run Control System stand-alone control unit. 




Photo 2: HCS prototype circuit board. 



APRIL 1985 "BYTE 



105 



CIRCUIT CELLAR 



nector has been provided to which an 
auto-answer modem can be attached 
(such as the Hayes 300 or 1200). 
When the modem answers and the 



CTS line is activated, the HCS switches 
its display to the modem data rate 
and allows the remote calling terminal 
to access and control the HCS. Unlike 



FRI APR 



8:94 PM 



ALARM SYSTEM ON 

MOTION DETECTED IN STOCK ROOM 

LIGHTS TURNED ON 

SILENT ALARM 

SECURITY NOTIFIED 



1111111 
1234567898123456 
1 BSR ON/OFF A 1111 
£ BSR DIMMER A 

3 BSR CYCLER A 

4 BSR OH/OFF B 

5 BSR ON/OFF C 

6 DIRECT OUT 

7 MESSAGES 1 

3 SUPERKEY " 



Photo 3: A typical status-display screen. At the top, the screen shows that an alarm 
has been triggered and that several preprogrammed actions have taken place. The bottom 
half of the screen indicates the status of all the output drivers. 



A REPORT, CREATE, OR DELETE EUENT 



D MANUAL RESTORE E AUTO RESTORE 

F RESTORE BY INPUT G SET DATE AND TIME 

H CLOCK ACCURACY I TIME FORMAT 

J TRACK SUNSET K DAYLIGHT SAUINGS 

I LIST EUENTS M SET LIST SPEED 



H **TOTAL RESET** LINES PER SCREEN 



P INPUT STATUS 



Q HOLD BY INPUT 



R DEFINE SUPERKEY S BYPASS MODULE 



T DELAY EUENT 



U SET BEEPER TIME 



U SET EUENT TO EXECUTE ONLY ONCE 
ENTER LETTER OF CHOICE <A-Z>? ■ 



Photo 4: The editing menu. You reach this screen from the status-display screen by 
pressing the space bar. All the functions will be explained in subsequent articles. 



auto-answer BSR units that allow com- 
mand input only, this option lets you 
view the complete status of all I/O and 
make program changes as well. 

The HCS can schedule to turn out- 
puts on or off based on combinations 
of the following conditions: 

a. time of the week (e.g., Tuesday 
at 4:32) 

b. time of the month (e.g., 22 nd at 
11:20) 

c. input line going high 

d. input line going low 

e. turn off after time delay (e.g., re- 
main on for 1 5 minutes) 

f. one-time action triggered by 
specific input or time 

When you want to create an event, 
various combinations of inputs and 
time can be specified. They are 

1. ON at specified time 
OFF at specified time 

2. ON at specified time 
OFF when specified input 
occurs 

3. ON when specified input occurs 
OFF at specified time 

4. ON when specified input occurs 
OFF when specified input 
occurs 

or 
ON while specified input occurs 

5. ON when specified input occurs 
OFF after period of time 

Lights can be dimmed to one of 16 
levels. This allows mood control, night 
light, or power conservation opera- 
tion. Text messages of variable size 
can be scheduled as announcements 
or reminders. And the HCS uses less 
than 5 watts (W). 

The processor and clock continue 
to operate during a power failure; 
scheduled events are noted in mem- 
ory. When AC power is restored, the 
HCS restores all modules to the state 
they would be in if power weren't in- 
terrupted. 

The on-time of desired modules, 
usually lights, tracks the sunset. This 
alleviates having to adjust the 
schedule many times per year as the 
sunset changes. Included is a com- 



106 BYTE' APRIL 1985 



CIRCUIT CELLAR 



mand to compensate sunset times for 
daylight saving. 

The HCS can optionally restore the 
status of all modules every four 
minutes. This is useful in commercial 
applications where a module may be 
turned off by a transient or non-HCS- 
generated command. Restore can 
also be triggered by an input line. 

Modules can be bypassed for a 
selected interval (up to 44 days). This 
can be used for vacations or holidays. 
It also allows an input occurrence to 
lock out specified modules. Clock ac- 
curacy can be adjusted by software to 
within one second per day And, final- 
ly, the entire event schedule can be 
listed to the serial port. The speed of 
the listing can be controlled to allow 
for printing of the schedule. 

The HCS is designed to communi- 
cate in English and not in a program- 
ming language. All control sequences 
are prompted through menus, and 
any input errors simply cause the sys- 
tem to revert back to the status dis- 
play or the option menu. 

The HCS is designed around the 
concept of an 'event." An event has 
four elements: the type of event, the 
device on which the event will 
operate, the trigger that starts the 
event, and the trigger that ends the 
event. The type of event is defined in 
terms of its "driver." These include 
Message Driver, BSR On/Off Driver, 
BSR Cycle Driver, BSR Dimmer Driver, 
Direct Output Driver, and Superkeys. 

The Message Driver displays a mes- 
sage on the terminal. The BSR On/Off 
Driver turns a BSR control module on 
or off. The BSR Cycle Driver causes 
a specified BSR module to cycle on 
and off periodically at a rate deter- 
mined by the user. The BSR Dimmer 
Driver changes the brightness of a 
BSR lamp module. The Direct Output 
Driver sets the output level on the 
eight direct output lines. Superkeys 
are 16 function keys that, when 
selected by a three-button sequence, 
trigger a predefined event sequence 
(such as turning on specific BSR 
modules, displaying particular mes- 
sages, or setting specific outputs). The 
quantity of events is limited only by 

{continued) 



Figure 2: Programming the HCS to turn the attic fan on. 
FRI APR 5 10:09 PM 



1111111 
1234567890123456 

1 BSR ON/OFF A 

2 BSR DIMMER A -- 

3 BSR CYCLER A 

4 BSR ON/OFF B - (When using a terminal, the raised- 

5 BSR ON/OFF C dot graphics character is printed 

6 DIRECT OUT - as a " - " instead) 

7 MESSAGES - 

8 SUPERKEY 

(a space entered on the keyboard brings up the editing menu) 

A REPORT,CREATE,OR DELETE EVENT 

B SET HOUSE CODE C MANUAL ON/OFF 

D MANUAL RESTORE E AUTO RESTORE 

F RESTORE BY INPUT G SET DATE AND TIME 

H CLOCK ACCURACY I TIME FORMAT 

J TRACK SUNSET K DAYLIGHT SAVINGS 

L LIST EVENTS M SET LIST SPEED 

N "TOTAL RESET** O LINES PER SCREEN 

P INPUT STATUS Q HOLD BY INPUT 

R DEFINE SUPERKEY S BYPASS MODULE 

T DELAY EVENT 

U SET EVENT TO EXECUTE ONLY ONCE 

ENTER LETTER OF CHOICE (A-Z)? A 

* MEANS EVENTS ARE SCHEDULED 

1111111 
1234567890123456 

1 BSR ON/OFF A ■■.■■ , ,- ■ ■■ - 

2 BSR DIMMER A - ----- 

3 BSR CYCLER A - 

4 BSR ON/OFF B (No events are 

5 BSR ON/OFF C - ----- presently scheduled) 

6 DIRECT OUT 

7 MESSAGES -- 

8 SUPERKEY 

ENTER DRIVER NUMBER (1-8)? 1 

ENTER MODULE NUMBER (1-16)? 1 

THIS DRIVER/MODULE NOT IN USE 

CREATE OR DELETE EVENT (C/D)? C 
374 CHARACTERS AVAILABLE 

ENTER NAME OF MODULE 

ONE RETURN STARTS NEW LINE 
AND TWO RETURNS ENDS 
?ATTIC FAN 

1 ON AT SPECIFIED TIME 
OFF AT SPECIFIED TIME 

2 ON AT SPECIFIED TIME 

OFF WHEN SPECIFIED INPUT OCCURS 



ON WHEN SPECIFIED INPUT OCCURS 
OFF AT SPECIFIED TIME 



[continued) 



APRIL 1985 -BYTE 107 



CIRCUIT CELLAR 



By selecting 



different options 
you can program 
the HCS to perform 



specific tasks. 



the available RAM (random-access 
read/write memory). (Even though the 
Superkeys. messages, and outputs are 
not BSR devices, I refer to each of 
their separate events as modules to 
be consistent with BSR terminology} 

The HCS has two display modes: 
status and editing. The status display 
shown in photo 3, is the normal oper- 
ating display of the HCS. At the top 
is the current date and time. Below 
that is an area where any messages 
will be displayed when activated. At 
the bottom is the actual real-time 
status of all output drivers presented 
as an 8-driver by 16-module display 
matrix. If no action has been defined 
for a particular module a raised dot 
is displayed. If an event has been pro- 
grammed for a particular module, a 
"0" indicates that it is currently off; 
a T 1 indicates that it is currently on. 
The display updates in real time as 
the modules change state or the clock 
updates. 

Pressing the space bar displays the 
editing menu (see photo 4). By select- 
ing the different options presented in 
the menu, you can program the HCS 
to perform the specific tasks you wish. 
Controlling the attic fan with two 
thermostatic switches attached to in- 
put lines 1 and 2 respectively is a rel- 
atively simple procedure. Figure 2 
shows what appears on the display 
screen as we program that event. 

The fan will start when input line 1 
goes low (it can be redefined for 
reverse polarity) and will go off when 
line 2 goes low. Perhaps you want to 
know when the fan is on (besides re- 
membering that driver 1 /module 1 is 
the fan and looking at the status dis- 
play), so we'll add a message defined 



4 ON WHEN SPECIFIED INPUT OCCURS 
OFF WHEN SPECIFIED INPUT OCCURS 

5 ON WHEN SPECIFIED INPUT OCCURS 
OFF AFTER PERIOD OF TIME 

ENTER NUMBER OF ON/OFF 
COMBINATION (1-5)? 4 

ENTER INPUT # FOR ON (1-16)? I 

ENTER INPUT # FOR OFF (1-16)? 2 



(Entering the same input # for 
both the ON and OFF trigger 
in Item 4 results in "ON WHILE 
SPECIFIED INPUT OCCURS") 



ATTIC FAN 
1 INPUT# 



1 



INPUT# 2 



ENTER INPUT # FOR ON (1-16)? (More inputs can be added to specify 

the same BSR module function; to exit, 
simply enter a return and the status 
display will resume) 

FRI APR 5 10:11 PM 



1111111 
1234567890123456 

1 BSR ON/OFF A 

2 BSR DIMMER A — (Status display now 

3 BSR CYCLER A - shows driver 1 module 

4 BSR ON/OFF B - 1 programmed but 

5 BSR ON/OFF C - inactive) 

6 DIRECT OUT - 

7 MESSAGES ----- 

8 SUPERKEY - - 



Figure 3: Programming the HCS to print a message when the fan is on. 
* MEANS EVENTS ARE SCHEDULED 

1111111 

1234567890123456 

1 BSR ON/OFF A * 

2 BSR DIMMER A - 

3 BSR CYCLER A - — 

4 BSR ON/OFF B — 

5 BSR ON/OFF C — - 

6 DIRECT OUT 

7 MESSAGES 

8 SUPERKEY 

ENTER DRIVER NUMBER (1-8)? 7 
ENTER MODULE NUMBER (1-16)? 1 
THIS DRIVER/MODULE NOT IN USE 
CREATE OR DELETE EVENT (C/D)? C 

1 ON AT SPECIFIED TIME 

OFF AT SPECIFIED TIME ^^ 



108 BYTE' APRIL 1985 



CIRCUIT CELLAR 



2 ON AT SPECIFIED TIME 

OFF WHEN SPECIFIED INPUT OCCURS 

3 ON WHEN SPECIFIED INPUT OCCURS 
OFF AT SPECIFIED TIME 

4 ON WHEN SPECIFIED INPUT OCCURS 
OFF WHEN SPECIFIED INPUT OCCURS 

5 ON WHEN SPECIFIED INPUT OCCURS 
OFF AFTER PERIOD OF TIME 

ENTER NUMBER OF ON/OFF 
COMBINATION (1-5)? 4 

ENTER INPUT # FOR ON (1-16)? 1 

ENTER INPUT # FOR OFF (1-16)? 2 

502 CHARACTERS AVAILABLE 

ENTER MESSAGE 

ONE RETURN STARTS NEW LINE 
AND TWO RETURNS ENDS 
? 

THE ATTIC FAN IS ON 



1 INPUT# 1 
THE ATTIC FAN IS ON 



INPUT# 2 



ENTER INPUT # FOR ON (1-16)? (just return to exit) 
FRI APRS 10:12 PM 



1111111 
1234567890123456 

1 BSR ON/OFF A - - 

2 BSR DIMMER A — 

3 BSR CYCLER A - - -- 

4 BSR ON/OFF B (The two zeros indicate that the 

5 BSR ON/OFF C modules are defined but OFF) 

6 DIRECT OUT 

7 MESSAGES 0-- - 

8 SUPERKEY 

(If we close the contact on input line #1 , the following happens:) 
FRI APR 5 10:15 PM 
THE ATTIC FAN IS ON 



(This listing is spaced to show 
the full 24-line display) 



1111111 
1234567890123456 

1 BSR ON/OFF A 1 -- 

2 BSR DIMMER A 

3 BSR CYCLER A ----- ---- 

4 BSR ON/OFF B - 

5 BSR ON/OFF C -- 

6 DIRECT OUT 

7 MESSAGES 1 

8 SUPERKEY 



As I use the HCS 
and find certain 
functions or displays 
I want revised, some 
of them may change. 



to trigger from the same events to say 
"the fan is on." 

We can create an event at this point 
by simply typing "A." The display that 
results is shown in figure 3. 

There is a lot more to this control 
system than the simple example in 
figure 3 illustrates. You probably no- 
ticed functions such as Restore, 
Sunset Adjust, Delay, Bypass, and 
Hold in the editing menu. Eventually, 
I'll get to explaining them all and il- 
lustrating their use. 

One Parting Comment 

The HCS is an evolving design. This 
is a three-month project that is being 
written over the course of three 
months. While the hardware design is 
fixed and printed-circuit boards are 
checked out, software is constantly 
evolving and more features are being 
added. Photos of the menus, status 
displays, and other items are taken at 
a specific time in the evolution of the 
software. As I use the HCS and find 
certain functions or displays that I 
want revised, some of them may 
change. 

User-friendliness is one area. In 
reviewing some of the higher-volume 
but lower-functioning control systems 
such as GE's HomeMinder, the em- 
phasis is on graphics and simple user 
interfacing. If you want to control a 
lamp on the HomeMinder, you look 
for the picture of a lamp and manip- 
ulate it on the screen. 

I configured HCS to be a high-level 
controller with much less emphasis 
on pretty graphics. However, many of 
the professional software people who 
have seen HCS believe it would have 

{continued) 



APRIL 1 985 • BYT t 109 



CIRCUIT CELLAR 



a much wider audience if it had some 
"paint-by-numbers" appearance. Con- 
sequently, they plan to support it in- 
dependently A HomeMinder-like 
graphics package is presently being 
written for the IBM PC by third par- 
ties. It will connect to the HCS through 
the terminal I/O port. Hopefully I'll 
have a picture of it in operation by the 
third month. 

While I'll live without Alice-in- 
Wonderland control software 1 was 
bitten by the large-system interface 
bug and decided to take advantage of 
big-system functions. The HCS op- 
tionally includes an upload/download 
capability to the IBM PC (eventually 
for other computers). The complete 
command and control sequence resi- 
dent in the HCS can be uploaded 
serially to the PC for storage on disk. 
A download provision reprograms the 
HCS with that control sequence. 

This storage capability allows the 
user to run the HCS with various con- 
trol sequences loaded from disk. A 
"training" session debugs the se- 
quence and then it is stored on disk 
for later retrieval. Industrial users who 
change program sequences frequent- 
ly are the prime beneficiaries, but new 
tools often produce new applications. 
This function is also accessible via the 
HCS's modem port, and Home Run 
can be completely reprogrammed by 
telephone. (Perhaps you have a vaca- 
tion home. Simply call ahead and let 
the HCS make it a warm and cozy 
arrival.) 

Experimenters and 
OEM Users 

As always, I try to support the com- 
puter experimenter by providing 
sources for many of the components. 
The Circuit Cellar Home Run Control 
System is a single-board design suit- 
able for OEM applications as well. It 
is available in various configurations 
that are all ultimately upgradable to 
the same potential. 

If you plan on building the unit from 
scratch, good luck and take heart. 
Send me a picture of your board, and 
I'll send you a free hexadecimal dump 
(16K bytes) of the control software, 
provided it is for noncommercial 



private use. I'll supply the code on 
two 2764 EPROMs (erasable pro- 
grammable read-only memories) and 
a manual for $32 (postpaid in the 
U.S.). Add $7 for overseas. 

Circuit Cellar Feedback 

This month's feedback begins on 
page 408. 

Next Month 

This is a three-part article. Next 
month, I'll describe the hardware in 
detail, hopefully to the extent that you 
can build your own HCS. The third 
part will emphasize the software and 
demonstrate a typical control appli- 
cation. ■ 

ROBOTIC PROPS (counterclockwise from 
upper left): 1. Cybot Inc., 12510 128th 
Ave. NE, Kirkland, WA 98034. 2. Microbot 
Inc., 453 Ravendale Dr., Mountain View, 
CA 94043. 3. Haikato Robotics Ltd.. 
1580 Lincoln St., Suite 950, Denver CO 
80203. 4. Heath Co., Hilltop Rd., St. 
Joseph. Ml 49085. 5. RB Robot Corp., 
14618 West 6th Ave, Golden. CO 80401. 
6. RSI Inc. (Robotics Systems International 
Ltd.). 9865 West Saanich Rd., RR2. Sydney. 
British Columbia V8L 3S1, Canada. 7. 
Hubotics Inc., 63 52-D Corte Del Abeto, 
Carlsbad, CA 92008. 8. Rhino Robots 
Inc., POB 4010. Champaign. IL 61820. 




SET PROPS: Sturbridce Yankee Work- 
shop Inc., Kettleford Korner. Bedford, NH 
03102. Britches of Concord Inc., 1 
Eagle Square. Concord. NH 03301. Genie 
Vacuum Cleaner Co., 93 South Maple St., 
Manchester. NH 03103. 

Special thanks to Bill Summers and Leo Taylor 
for their software expertise. 



The following items are available from 

The Micromint Inc. 

2 5 Terrace Dr. 

Vernon, CT 06066 

(800) 635-335 5 for orders 

(203) 871-6170 for information 

1 . Home Run HCS— Complete assembled sys- 
tem with enclosure and Apple-compatible 
keyboard HCS01, $589 

2. Home Run HCS-Populated PC board. 
Assembled and tested PC board. No 
enclosure or keyboard HCS02, $429 

3. Home Run HCS— Video-based kit. Includes 
PC board and all components except 
enclosure, keyboard, and serial-interface 
components (IC16. 1C17, IC20, and two 
DB-2 5 connectors) HCSV05, $329 

4. Home Run HCS— Terminal-based kit. 
Includes PC board and all components ex- 
cept video-display processor {IC22. IC2 5, 
and IC26). No keyboard, enclosure, or RF 
modulator HCST06, $289 

5. 8K-byte static-RAM upgrade. Increases 
RAM to 16K bytes HCS20, $3 5 

6. Apple Il-compatible ASCII-encoded key- 
board HCS21, $79 

7. Wall transformer/transmitter module 
(available separately) HCS22, $40 

All kits and assembled units include 
operators manual, power supply with wall 
transformer/transmitter module, and 8K 
bytes of RAM. All units are supplied without 
keyboard encoder chip (not necessary when 
using encoded keyboard, 1C1 8— optionally 
available). All item numbers that list 
enclosures also include backup battery 
holder (6 "C" cells), less batteries. Serial-port 
and video-display-processor upgrades for 
items 3 and 4 and various other components 
are also available. 

Please include $8 for shipping and handling 
in the continental United States, $12 else- 
where. New York residents please include 8 
percent sales tax. Connecticut residents 
please include 7.5 percent sales tax. 

Editor's Note: Steve often refers to previous 
Circuit Cellar articles. Most of these past ar- 
ticles are available in book form from BYTE 
Books, McGraw-Hill Book Company POB 
400, Hightstown, NJ 082 50. 

Ciarcia's Circuit Cellar, Volume I covers articles 
in BYTE from September 1977 through 
November 1978. Volume 11 covers December 
1978 through lune 1980. Volume III covers July 
1980 through December 1981. Volume IV 
covers January 1982 through June 1983. 



To receive a complete list of Ciarcia's Cir- 
cuit Cellar project kits, circle 100 on the 
reader-service inquiry card at the back 
of the magazine. 



110 B YTE • APRIL 1985 



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Inquiry 184 



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by Colleen Roe Wilson 



Coprocessing 
in Modula-2 



The key to writing 
concurrent programs 
is coordination 



One of the main differences 
between Modula-2 and its 
ancestor, Pascal, is that 
Modula-2 contains specific program- 
ming constructs to permit the devel- 
opment of real-time concurrent pro- 
grams. Thus, you can use Modula-2 to 
write operating systems and other 
low-level software instead of using as- 
sembly language, the language in 
which operating systems are tradi- 
tionally written. 

Concurrency 

Thily concurrent programs execute at 
exactly the same instant in time- 
implying the use of separate com- 
puters. True concurrency occurs in 




distributed processors such as those 
found in control systems and other 
real-time applications. 

When several people use a single 
computer however, concurrency refers 
to interleaved execution. Such pro- 
gramming is at the heart of large time- 
sharing systems, where many users on 
a single computer can run programs 
at the same time. Each person per- 
ceives only the execution of his own 
program, while the operating system 
performs a juggling act partitioning 
the processing power among the 
users. Interleaved execution, then, is 
the seeming concurrency of many 
processes running on one processor. 

Whether we call it true concurren- 
cy or not, the problems inherent in 
writing this type of program are much 
the same. The main problem is tim- 
ing. Concurrent programs must deal 
with nondeterministic events that oc- 
cur at arbitrary times. 

Suppose you have two computers 
connected by some kind of commu- 
nications link. You want to write a pro- 
gram so that two people sitting in two 
different places can exchange mes- 
sages by typing at their respective 
keyboards. Each computer must per- 
form this basic sequence of actions: 

• When a key is struck on computer 
As keyboard, A must retrieve that 
key's value and send it to computer B. 

• When a character arrives at com- 
puter A from computer B, A must 

{continued) 
Colleen Roe Wilson (RR I, Campbelhille, 
Ontario LOP 1 BO, Canada) is a member of 
the technical staff at Allied Canada in 
Mississauga, Ontario. She has a B.S. and an 
M.S. in mathematics and enjoys gourmet 
cooking, gardening, and hiking. 



Inquiry 276 for Dealers. Inquiry 277 for End Users, 



ILLUSTRATED BY LAURA CORNELL 



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in 



COPROCESSING IN MODULA-2 



display it in the next free position on 
its screen. 

Does this sound simple enough? 
Let's take a look at what can happen. 
If you stop and think about how you 
type at a keyboard, it becomes ob- 
vious that you can't expect a fixed 
pattern to the keyboard input and the 
arrival of data on the link. Two users 
might carry on a question-and-answer 
conversation so that only one person 
types at a time. On the other hand, 
two users might argue and type 
simultaneously. Either way, the pro- 
gram needs to know what to do. This 
nondeterministic activity differen- 
tiates real-time programs from typical 
application programs with fixed 
read/write interfaces. You can't predict 
how many reads (input from the 
keyboard) or writes (output to the link) 
the program will have to deal with or 
how they will be ordered. 

The nondeterministic nature of con- 
current programming leads to some 
interesting problems— deadlock or 
"deadly embrace" being the best 
known. Suppose a time-sharing sys- 
tem is trying to run two programs. 
Both programs need exclusive use of 
the computer's tape drive and a par- 
ticular printer to run. The operating 
system starts program A, which ac- 
quires the tape drive. Having used its 
time slot, program A is suspended 
while the operating system starts pro- 
gram B. Program B immediately ac- 
quires the printer and is suspended. 
When A starts up again, it attempts 
to acquire the printer and fails, so its 
execution is suspended until the 
printer is freed. When B starts up 
again, it attempts to acquire the tape 
drive and is likewise suspended until 
the drive is freed. The two programs 
are deadlocked. Neither can proceed 
until the other frees the resource 
needed. 

The key to writing successful con- 
current programs is coordination. You 
must make sure that programs that 
are either cooperatively or indepen- 
dently executing interact with each 
other in a constructive— or at least 
nondestructive— manner. Modula-2 
has programming constructs dealing 



with concurrency 
coordination. 



to aid in this 



COPROCESSES 

Coprocessing is a technique that 
helps you implement coordination 
when writing concurrent programs. 
For example, suppose you write two 
programs to execute as coprocesses— 
Text and Disk. Text prompts you to 
enter text from the keyboard for disk 
storage (it could be an editor). Disk 
is a low-level driver program that in- 
teracts with the disk to read and write 
records. The two coprocesses interact 
as follows: 

• Text prompts you for keyboard in- 
put and puts the characters into a buf- 
fer as it receives them until it finds the 
record terminator. 

• Text signals Disk that a record is 
ready in the buffer and suspends 
execution. 

• Disk retrieves the record and writes 
it to the disk. 

• Disk signals Text that the record has 
been written and suspends its 
execution. 

• Text resumes execution at the point 
of suspension and prompts you for 
more input. 

Thus, Text and Disk coprocess the in- 
formation by passing it back and 
forth. This producer(Text)/consumer 
(Disk) relationship is the classic rela- 
tionship between coprocesses. 

You can expand this concept to in- 
clude more than two processes. Sup- 
pose you want various processes to 
exchange messages during execution. 
They need to be able to send mes- 
sages to other processes and to 
receive the same— a sort of electronic 
interprocess mail scheme. One spe- 
cial process is the postmaster. It 
receives and stores messages and 
then distributes them as requested by 
the designated receiving process. The 
postmaster acts as a coprocess with 
the other processes that can request 
to send or receive messages. When 
sending, the requesting process sus- 
pends execution while the postmaster 
picks up the message in its buffer and 
resumes when the postmaster is 
done. When receiving, the requesting 



process suspends while the post- 
master fills its buffer with the message 
and then continues. 

Writing Coprocesses 
in Modula-2 

Two essential mechanisms are needed 
to implement the mechanics of copro- 
cessing: first, a means of identifying 
and executing a program that estab- 
lishes it as a process; second, a 
method so that two coprocesses can 
signal each other to coordinate their 
activities. Modula-2 has facilities for 
these mechanisms imbedded within 
it. Modula-2 programmers do not 
have to get around the language to 
write coprocesses; the language 
directly supports this kind of pro- 
gramming. 

The most fundamental support of 
coprocesses provided in Modula-2 is 
the data type PROCESS, which can 
be imported from the module SYS- 
TEM. We expect languages to support 
our abstract number systems with 
such data types as REAL and IN- 
TEGER, but this is something new; a 
process materialized in a data type. 
The need for it is obvious: a language 
that manipulates processes must be 
able to refer to them in a concrete 
manner. 

Coprocesses use these PROCESS 
variables to communicate with each 
other. Therefore, when you create a 
coprocess, you must bind it to one of 
these variables. Likewise, when these 
programs pass control to one an- 
other, they must use PROCESS 
variables to indicate their targets. 
Modula-2 contains two procedures 
that provide this control: NEW- 
PROCESS and TRANSFER, both of 
which are imported from the module 
SYSTEM. 

NEWPROCESS, which creates a co- 
process within the system and binds 
it to a PROCESS variable, is called by 

NEWPROCESS(p: PROC,a: 
ADDRESS.s: CARDINAL.VAR c: 
PROCESS); 

In this statement, p is the name of a 
procedure that contains the code you 
want to constitute the process, a is the 

{continued) 



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COPROCESSING IN MODULA-2 



address of a storage area that serves f 
as the working space for the process 
(local data and context are stored in 
it), s is the size of the working space, 
and c is a PROCESS variable that 
NEWPROCESS sets to the value of 
the coprocess it creates. 

TRANSFER is the procedure that 
transfers control from the calling co- 
process to the one called. It is invoked 
by 

TRANSFERER 
thisprocess.coprocess: 
PROCESS); 

When a TRANSFER takes place, the 
calling coprocess is suspended and its 
context (data values, current program 
counter, etc.) saved. When the called 
coprocess executes the reverse 
TRANSFER, the calling program 
resumes execution at the point im- 
mediately following its just-executed 
TRANSFER statement. This is the 
significant difference between proce- 
dural calls and TRANSFERS. Each 
time you call a procedure, execution 
returns to the beginning of the pro- 
gram and local storage is reallocated. 
Coprocesses maintain context be- 
tween TRANSFERS. 

The actual implementation of the 
data type PROCESS and the proce- 
dures NEWPROCESS and TRANS- 
FER varies with each machine and 
compiler. However, you need not be 
concerned with this. The data abstrac- 
tion provided by Modula-2 lets you 
merely manipulate the PROCESS 
variables with these procedures. Your 
interface is constant across machines. 
Contrast this with assembly-language 
programming, where you need signifi- 
cant knowledge of the operating-sys- 
tem internals to manipulate the data 
structures representing processes. 

Coding an Example 

Now that we've established what facil- 
ities exist in Modula-2 to program co- 
processes, let's look at an example. 
Starting at the top of the module def- 
inition of TermHandler (see listing 1), 
you import the needed concurrency 
structures from SYSTEM: the data 
types PROCESS, ADDRESS, and 
WORD, and the procedures NEW- 



Listing I: An example of coprocesses coded in Modula-2. 

MODULE TermHandler; 
FROM SYSTEM IMPORT ADDRESS. PROCESS, NEWPROCESS, TRANSFER, 

WORD. ADR. SIZE; 
FROM SYSIO IMPORT GetChar, PutDisk; 
CONST bufsize = 80. 
nterm = 16; 
CR = 13C; 
TYPE buftype* ARRAY[0..bufsize-1] OF CHAR; 
VAR buffer: buftype; 
nchar: INTEGER; 

wspT: ARRAY[0..nterm-1],[1..200] OF WORD; 
wspD: ARRAY[1..200] OF WORD; 
D.C: PROCESS; 

T: ARRAY[0..nterm-1] OF PROCESS; 
thisterm: INTEGER; 
PROCEDURE Textln; 
VAR newchar: CHAR; 
Status: BOOLEAN; 
localbuf: buftype; 
count: INTEGER; 
BEGIN 
count: = - 1 ; 
LOOP 
GetChar(thisterm, newchar, status); 
IF status THEN 
CASE newchar OF 
CR: nchar: = count; 
buffer: = localbuf; 
TRANSFER(T[thisterm].D): 
count: = - 1 
ELSE 
INC(count); 

localbuf[nchar]: = newchar; 
IF count « buf size - 1 
THEN 

nchar; = count; 
buffer: = localbuf; 
TRANSFER(T[thisterm],D); 
count: = - 1 
END 
END 
END; 

TRANSFER(T[thisterm],C) 
END, 
END Textln; 
PROCEDURE TextToDisk; 
BEGIN 
LOOP 
PutDisk(buffer, nchar); 
TRANSFER(D,T[thisterm]) 
END 
END TextToDisk; 
BEGIN 
NEWPROCESS(TextToDisk,ADR(wspD),SlZE(wspD),D); 

FOR thisterm: = TO nterm - 1 DO 
NEWPROCESS(Textln,ADR(wspT[thisterm]), 

SIZE(wspT[thisterm]),T[thisterm]) 



{continued) 



116 BYTE • APRIL 1985 



COPROCESSING IN MODULA-2 



END; 

thisterrn: = 0; 
LOOP 

TRANSFER(C,T[thisternn]); 

thisterm:=thisterm + 1 MOD nterm 
END 
END TermHandler. 



PROCESS, TRANSFER, ADR, and 
SIZE. ADDRESS and WORD are self- 
explanatory primitive data types, 
ADR is a function that returns the ini- 
tial address of the variable passed to 
it, and SIZE is a function that returns 
that variable's storage allocation size. 
Assume the existence of a module 
named SYSIO, from which you import 
GetChar and PutDisk. In the CONST 
section you define the buffer size (buf- 
size) and the record terminator CR 
(carriage return). In the VAR section 
you define the shared buffer (buffer) 
and the shared character count 
(nchar). In addition, you define work- 
ing spaces for the two coprocesses 
you will create (wspT and wspD). 

Suppose you want to handle key- 
board-to-disk transfers for a number 
of terminals— an order-entry system, 
for example. Listing 1 shows an array 
of processes (T) and working spaces 
(wspT). The procedure GetChar is 
passed a terminal-port number (this- 
term) and returns a status (true means 
new character returned while false 
means the opposite) as well as the 
keyboard character (newchar). If a 
character has arrived since the last 
GetChar call it is returned; otherwise 
the status reports the failure. The rea- 
son will become clear in a moment. 

As the main body of code for Term- 
Handler begins, process D is created, 
followed by the nterm terminal pro- 
cesses. Then the program enters a 
loop continually coprocessing with 
each of the individual terminal 
handlers. Each one manages its own 
character count (count) and buffer 
(localbuf). When a handler detects a 
CR or a full buffer, it moves its own 
buffer and count to the global buffer 
(buffer) and global count (nchar) and 
transfers to process D to dump the 
record. (Although it is more common 
for coprocesses to share pointers to 



variables than actual variables, these 
examples use them to make the code 
more readable.) You can see that if 
GetChar waited for a character to 
arrive— in other words, if it did not use 
the status— a single terminal could 
hold up all the others if it produced 
no input. 

What does coprocessing achieve in 
this example? First, when a specific 
terminal handler issues a TRANSFER 
back to process C its context is saved 
in its workspace. Therefore, the next 
time it is activated, the values of count 
and localbuf are appropriately set. 
This would not be true if you used 
procedural calls instead of co- 
processes. 

Second, because each handler 
maintains its own data structures, the 
overall program is kept fairly simple. 
You don't have to manage an array of 
buffers and counters. Each handler is 
concerned with only a single buffer 
and counter, and the code is recycled 
nterm times. You also gain flexibility. A 
more sophisticated version of Term- 
Handler could associate processing 
priorities with some terminals and 
choose to ignore others. In fact, in a 
coprocessing situation TermHandler 
could create new terminal handlers on 
request (instead of using a fixed 
number) or only transfer to a specific 
handler on certain conditions. 

Conclusion 

Coprocesses cooperatively process 
information by interleaved execution 
on a single computer. You must be 
careful to ensure that processes inter- 
act constructively and Modula-2 auto- 
matically contains the programming 
constructs to aid in this coordination. 
These coprocesses provide a means 
of passing control between programs 
without losing the desired execution 
sequence or the context, a 




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Inquiry 132 APRIL 1985 • BYTE 119 




by James Hawley 



A MILLION-POINT 
GRAPHICS TABLET 



How to build low-cost graphics for the Z-100 



The following is a list of the parts used in JWMM| he need for a graphics 
this project and the price paid for each. This * * tablet is quickly apparent if 

project can be built for less than $180. you try to Jo high-resolu- 

1 KoalaPad $99 00 -™" tJOn drawin S s from a ke ^ 

1 S-100 Proto card'. . . '. . . '. '. . '. . '. ". . 1 5.00 b ? ard Although you can create com- 

2 ADC1001 A/D converter ICs* .... 60.00 P 1 ^ pictures with the control keys and 

2 20-pin sockets 50 cursor, you will soon want a true draw- 

2 14-pin sockets 50 ing machine because of the direc- 

I 16-pin socket. 2 5 tional and speed limitations of key- 

1 74LS20 dual 4 input nand 50 board drawing. 

1 74LS04 hexadecimal inverter 50 T . v nn :+u 7 inn ;„ ^,,1,, ^ ,-^^uia* 

1 7805 + 5-volt regulator 75 The Z f mth . ^Sn^ -K, g P . 

1 ioo^f capacitor 50 computer with 640 by 22 5 pixels in 

l/4-watt resistors: 1.00 three planes (eight colors). The 

2 10k ohm machine devotes 64K bytes to each 

i 8.2k ohm plane and has the ability to create 640 

1 15k ohm by 480 pixels in eight colors. The 

1 33Qohm ZBAS1C graphics commands offer a 

$178.50 quick method of creating custom 

graphics programs. 
* available from: DigHCey Tq ^^ tme hjc creativity you 

Highway 32 South . «. . , c . „ „ 

orTn at? neec l to use a stylus for input. You can 

Pud 677 . , ,. , • . . * 

Thief River Falls, draw with a light pen but it is often 

MN 56701 awkward to use vertically and difficult 

(800) 346-5144 to tell exactly where the pen is point- 

ing on a pixel-by-pixel basis. A graph- 
ics tablet solves these problems. 

There are many methods of inter- 
facing analog input to a microcom- 
puter's bus but it is simplified by 

}ames Hawley (4272 Queens Ave. South, 
Minneapolis, MN 55410) is the president of 
laminar Flow inc. in Minneapolis. He enjoys 
flying gliders and designing computer-graphics 
hardware and software. 



bus-compatible analog-to-digital (A/D) 
converters. The National Semiconduc- 
tor ADC 1001 enables you to interface 
a 10-bit digital (1024-point) signal to 
the Zenith S-100 bus with only two 
support chips. 

The graphics pad described here 
uses Koala Technologies' KoalaPad for 
the analog x, y input that feeds the 
two ADClOOls connected to the S-100 
bus. To modify the KoalaPad, you 
open it by unscrewing the screws on 
the bottom, holding the unit together 
and flipping it over, and then lifting 
the pad away from the circuit board. 
Remove the black and blue wires from 
the bottom of the board and, with 
wire-wrap wire, solder them onto pins 
4 and 9 (respectively) of the chip on 
the lower left side of the circuit board 
(next to resistor number 23). These 
two lines will now carry the 0-3-volt 
analog signal (see photo 1). Tape the 
wires out of the way and gently 
replace the pad. Then put on the 
cover, turn the unit over, and screw it 
back together. The KoalaPad is now 
ready to plug into the empty socket 
on the S-100 card. A brief description 
of the circuit is shown in figure 1 . You 
can use the wire-wrap wire-and-solder 
method to build the board but the 3M 
press-pin method is easier. It allows 
rapid assembly and disassembly. The 
3M socket and insertion tool make up 



120 B YTE • APRIL 1985 



the 3M wiring system, which is sold 
as the Whiz Kit by Ragon Inc. of Min- 
neapolis, Minnesota. Its ease and 
speed justify the high cost of the 
sockets. 

Listing 1 gives you all the program- 
ming necessary to get the x, y values 
you need for drawing or cursor move- 
ment from the circuit board. If you in- 
tend to compile the program, it is a 
good idea to repeat the OUT and INP 
routines and compare the values you 
get. This error checking is helpful 
because the KoalaPad can generate 
some bogus values because of the ex- 
ecution speed of compiled code. 

If the ZBASIC language were 
changed to take full advantage of the 
interlace mode then Zenith would be 
able to offer true high-resolution color 
graphics at the lowest price in the 
industry ■ 



Listing I: This program is all you 
need to access the KoalaPad. 

10 'LISTING #1 

20 OUT 127,0 START CONVERSION 
30 A = INP(127) 'INPORT TOP 8 BITS 
40 B = INP(127) IN BOTTOM 2 BITS 
50 A = A*4:B = B/64:X = A + B '10 BITS 
60 OUT 126,0 'START CONVERSION 
70 A = INP(126) 'INPORT TOP 8 BITS 
80 B = INP(126) 'IN BOTTOM 2 BITS 
90 A = A*4:B = B/64:Y = <A + B)/4 



S-100 




A7 [£T>- 



OUT [4T>- 
INP [46^ 



DATA / 
IN \ 



+8vrr>- 

GNd[50>- 



11 



JP 



+ 5V 



IC1 
74LS04 



10 



18 



17 



16 



15 



14 



13 



12 



11 



r fh 



IC3 
ADC1001 



+ 5V 



20 



20 



19 



10 



10 



IC4 

ADC 1001 



10K 



;iso 

PF 



m 



IC2 

74LS20 



T 



+ 5V 

t 



+ 5V 



10 



BLK 

16 -PIN 

SOCKET 

APPLE 



BLU 



X 



+ 5V 



+ 5V 



7805 



+8V 



'8.3K 



1 >1.53K 

;±^150pF 



1 



Figure I: The 74LS04 inverts address signals to the 74LS20 to create two chip-select 
signals for the two ADClOOls (U3 and U4). \t also inverts the OUT and INP lines 
and sends their signals to UJ and U4 as WR and RD. The clocks on pins 19 and 4 
of the ADClOOls use a resistor capacitor circuit, and reference voltage for the circuit 
comes from resistors across CRD and +5. 



APRIL 1985 'BYTE 121 



$49 95 










SOMETHING BRAND NEW 



INSTANT DATABASES . . . BECAUSE THAT'S 
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THE TOOLS YOU NEED. 



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even when you're working in 


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• Template Maker (for designing 


• Notepad 


your own databases) 


• Time and Expense Diary 


• DOS Services 


• Programmable Hotkey (You 


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choose the key that gets you 


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databases or your other 


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• Cut and Paste (great for putting 


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letter that combines a chunk of 


• Alarm Clock (including Musical 


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document, and a few notes) 


• To-Do List 





122 BYTE • APRIL 1985 



HE EXCITEMENT IS BACK 

With the Electronic Mailbag of Your Dreams 

ELECTRONIC MAIL THAT TAKES CARE OF ITSELF ... IN THE BACKGROUND 

(While you're running WordStar, Lotus, dBase, a compiler or whatever) 

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j always felt that there was something strange about having to play postman every time a piece of electronic mail was due. 
\ was always a case of loading up a communications package and either waiting for the mail or going out to fetch it. 
Now, we've got it! And you can have it, too. With HOMEBASE, Electronic mail can arrive while you're working in another piece of 
software. Up in the corner of your screen, a signal lets you know that there's incoming mail. You can read it as it comes in, if you 
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When you're sending Electronic Mail, its just as easy. Once you've written and addressed your letter, the rest is done for you, 
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Inquiry 22 



Sidekick is a trademark of Borland Interntlonal. inc Poly Windows is a trademark of Polylron Corp. Spotlight is a trademark of Software Arts. 

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Tables and Pages 
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Instant Databases 








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Cut and Paste 








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llf 



BYTE 



Artificial 
Intelligence 



Communication with Alien Intelligence 
by Marvin bAinsky . 1 26 

The Quest to Understand Thinking 

by Roger Schank and Larry Hunter 143 

The LISP Tutor 

by \ohn R. Anderson and Brian J. Reiser . . 159 

PROUST 

by W. Lewis ]ohnson and Elliot Soloway ... 1 79 

Architectures for AI 

by Michael F. Deering 193 

The LISP Revolution 

by Patrick H. Winston 209 

The Challenge of Open Systems 

by Carl Hewitt 223 

Vision 

by Dana H. Ballard and 

Christopher M. Brown . . 245 

Learning in Parallel Networks 

by Geoffrey E. Hinton 265 

Connections 

by ]erome A. Feldman 277 

Reverse Engineering the Brain 

by John K. Stevens 286 

The Technology of Expert Systems 

by Robert H. Michaelsen. Donald Michie, 

and Albert Boulanger 303 

Inside an Expert System 

by Beverly A. Thompson and 

William A. Thompson 315 



YOU AWAKE ONE MORNING to find your brain has another lobe function- 
ing. Invisible, this auxiliary lobe answers your questions with information 
beyond the realm of your own memory suggests plausible courses of action, 
and asks questions that help bring out relevant facts. You quickly come to 
rely on the new lobe so much that you stop wondering how it works. You 
just use it. This is the dream of artificial intelligence. In this issue of BYTE, 
a group of distinguished authors, including leading researchers, examine the 
state of this challenging field. While the auxiliary lobe is a distant dream, some 
of these articles show that AI has won a place on personal computers. 

Understanding artificial intelligence requires understanding intelligence itself. 
Marvin Minsky of MIT explores the concept of intelligence and considers 
whether we will be able to communicate with extraterrestrial intelligence when 
we encounter it. Some of the conceptual structures needed to make com- 
puters perform operations natural to the human mind are covered by Roger 
Schank and Larry Hunter of Yale. 

Computer science is among the first fields to benefit from AI. John Anderson 
and Brian Reiser of Carnegie-Mellon describe their interactive LISP program 
that teaches people to program in LISP, while Yale's Lewis Johnson and Elliot 
Soloway explain the operations of their LISP program that finds nonsyntactic 
bugs in Pascal programs. 

If we are to have powerful AI on personal computers, we must have efficient 
hardware and software. Michael Deering of Schlumberger Research surveys 
some efficient architectures for AI. After noticing the recent flowering of LISP 
on personal computers, MIT's Patrick Winston provides an introduction to the 
language. Carl Hewitt, developer of an early logic programming language, ques- 
tions whether logic programming will be able to develop intelligent systems 
for complex applications in the real world. 

In their article, Dana Ballard and Chris Brown of Rochester University explain 
how the miracle of vision rests on hierarchical representations of information 
as well as on parallel processing. Parallelism is explored further by Geoffrey 
Hinton of Carnegie-Mellon, who presents two theories of how learning could 
occur in brain-like networks. Jerome Feldman of Rochester elaborates on key 
issues in massive parallelism in both natural and artificial intelligence. John 
Stevens of the University of Tbronto takes a bold and intriguing look at the 
possibilities of copying the brain's own circuitry directly He starts with the device 
physics of the brain and goes on to discuss silicon-based designs. 

The methods for building expert systems discussed by Robert Michaelsen, 
Donald Michie, and Albert Boulanger include not only those based on rules 
but also those based on deeper representations of knowledge. Beverly and 
William Thompson explain a rule-based expert system written in Pascal. 

Space limitations prevented the inclusion of Michael Fichtelman's expert 
system in Logo and Phillip Robinson's description of a custom AI chip 
developed at Syracuse University. Look for these articles in forthcoming issues. 

Many of the technical terms used in the context of AI involve subtle varia- 
tions on the traditional computer science definitions. Please consult the 
glossary on page 138 for definitions of several of these terms. 

—Phil Lemmons, Editor in Chief 



APRIL 1985 -BYTE 125 




♦ 


* • 

•• 


• 


.• 








1 --^^ 




c 


D 

C 







R 





126 B YTE • APRIL 1985 



ILLUSTRATED BY JAMES ENDICOTT 



ARTIFICIAL INTELLIGENCE 



COMMUNICATION 

WITH ALIEN 

INTELLIGENCE 



by Marvin Minsky 



It may not be as difficult as you think 



WHEN FIRST WE MEET those aliens 
in outer space, will we and they be 
able to converse? I believe that, yes, 
we will— provided they are motivated 
to cooperate— because we'll both 
think in similar ways. I propose two 
kinds of arguments for why those 
aliens may think like us, in spite of 
having very different origins. These 
arguments are based on the idea that 
all intelligent problem solvers are sub- 
ject to the same ultimate constraints- 
limitations on space, time, and 
materials. For animals to evolve 
powerful ways to deal with such con- 
straints, they must have ways to repre- 
sent the situations they face, and they 
must have processes for manipulating 
those representations. These two re- 
quirements are: 

Economics: Every intelligence must 
develop symbol systems for repre- 
senting things, causes, and goals, and 
for formulating and remembering the 
procedures it develops for achieving 
those goals. 

Sparseness: Every evolving intelli- 
gence will eventually encounter cer- 
tain very special ideas— e.g., about 



arithmetic, causal reasoning, and 
economics— because these particular 
ideas are very much simpler than 
other ideas with similar uses. 

The economics argument is that the 
power of a mind depends on how it 
manages the resources it can use. The 
concept of thing is indispensable for 
managing the resources of space and 
the substances that fill it. The concept 
of goal is indispensable for managing 
how we use the time we have avail- 
able—both for what we do and what 
we think about. Aliens will use these 
notions too, because they are both 
easy to evolve and because there ap- 
pear to be no easily evolved alter- 
natives for them. 

The sparseness theory tries to make 
this more precise by showing that 
almost any evolutionary search will 
soon find certain schemes that have 
no easily accessible alternatives, that 
is, other different ideas that can serve 
the same purposes. These ideas or 
processes seem to be peculiarly 
isolated in the sense that the only 
things that resemble them are vastly 
more complicated. I will discuss only 



the specific example of arithmetic and 
conjecture that those other concepts 
of objects, causes, and goals have this 
same island-like character. 

Critic: What if those aliens have 
evolved so far beyond us that their 
concerns are unintelligible to us and 
their technologies and conceptions 
have become entirely different from 
ours? 

Then communication may be in- 
feasible. My arguments apply only to 
those stages of mental evolution in 

{continued) 
Artificial-intelligence pioneer Marvin Minsky 
is Donner Professor of Science in the Depart- 
ment of Electrical Engineering and Computer 
Science at Massachusetts \nstitute of Tech- 
nology (545 Technology Square, Cambridge, 
MA 02139). Ik the late 1950s, Minsky, 
together with John McCarthy [now at Stan- 
ford), created MIT's AI laboratory, of which 
Minsky was the director for several years. 
Minsky has long been interested in SETI [the 
Search for Extraterrestrial Intelligence) and 
participated in the important 1971 conference 
on communication with extraterrestrials, held 
in Soviet Armenia and organized by Carl 
Sagan. 



APRIL 1985 -BYTE 127 



COMMUNICATION 



A distinctive aspect 
of intelligence is 
the ability to solve 
new, different problems. 



which beings are still concerned with 
surviving, communicating, and ex- 
panding their control of the physical 
world. Beyond that, we may be unable 
to sympathize with what they come 
to regard as important. Yet even then 
we can hope to communicate with the 
mental mechanisms they use to keep 
account of space and time; these 
could remain as sorts of universal 
currency. 

Critic: How can we be sure that things 
like plants and stones or storms and 
streams are not intelligent in other 
ways? 

If you can't say in what respects 
their intelligence is similar, it makes no 
sense to use the same word. They cer- 
tainly don't seem good at solving the 
kinds of problems that challenge our 
intelligence. 

Critic: What's so special about solv- 
ing problems? Please define intelli- 
gence precisely so that we'll know 
what we are discussing. 

It's not one author's place to tell 
other people how to use a word that 
they already understand. Let's just use 
intelligence to mean what people 
usually mean: the ability to solve hard 
problems— like how to build space- 
ships and long-distance communica- 
tion systems. 

Critic: Then please define what a hard 
problem is. For instance, we know that 
human intelligence was involved in 
building the pyramids— yet coral-reef 
animals build things on an even larger 
scale. Should we therefore be able to 
communicate with them? 

No. Humans do indeed solve such 
problems, but it is only an illusion that 
coral-reef animals do. An important 
factor is .speed. No single bird dis- 



covers how to fly: Evolution used a 
trillion bird-years to find out how— yet 
man learned to fly in tens of human- 
years. And while a person might take 
several years to find a way to build a 
structure like an oriole's nest or a 
beaver's dam, no oriole or beaver 
could ever learn to do such things at 
all without exploiting the ancient nest- 
machines their genes construct inside 
their brains. A distinctive aspect of 
what we call intelligence is this ability 
to solve a wide range of new, different 
kinds of problems. This is why it makes 
sense to try to communicate with an 
individual animal that can leam quickly 
how to solve new hard problems. 

What enables us to solve hard prob- 
lems so quickly? Here are some ingre- 
dients that seem to me so essential 
that 1 would expect intelligent aliens 
to use them, too: 

Subgoals—to break hard problems 
into simpler ones 

Subobjects—to make descriptions 
based on parts and relations 
Cause-symbols—to explain and 
understand how things change 
Memories— to accumulate experience 
about similar problems 
Economics— to efficiently allocate 
scarce resources 

Planning— to organize work before fill- 
ing in details 

Self-awareness— to provide for the 
problem solver's own welfare 

Still aren't these only a few of the 
myriads of other possibilities? Why 
can't our aliens do all such things in 
completely alien ways? 1 believe that 
these problem-solving schemes are 
not as arbitrary as they seem. 

The Sparseness Principle 

Why does it seem so obvious to us 
that two and two equal four? Such 
mysteries have long concerned philos- 
ophers—why certain concepts seem 
to come into our minds as though 
they need no prior experience or 
evidence. My answer is that this may 
be due at least in part, to the follow- 
ing computational phenomenon. 

The Sparseness Principle: Whenever 
two relatively simple processes have 



products that are similar, those prod- 
ucts are likely to be completely 
identical. 

Because of this, we can expect cer- 
tain a priori structures to appear, 
almost always, whenever a computa- 
tional system evolves by selection 
from a universe of possible processes, 
The ideas of number and arithmetic 
are examples of this, and my conjec- 
ture is that this may be why different 
people can communicate so perfect- 
ly about such matters, although their 
minds may differ in many other ways. 
This may apply to aliens, too. Let me 
explain the sparseness principle by re- 
counting two anecdotes. One involves 
a mathematical experiment, the other 
a real-life experience. 

A Mathematical Experiment— I 
once set out to explore the behaviors 
of all possible processes— that is, of 
all possible computers and their pro- 
grams. There is an easy way to begin 
that search: you just list all possible 
finite sets of rules, one by one. This 
is easy to do using methods that Alan 
Hiring described in 1936; these are 
what today we call "Hiring machines." 
Naturally, 1 didn't get very far because 
the variety of such processes grows 
exponentially with the number of 
rules in each set. However, with the 
help of my student, Daniel Bobrow, I 
managed to examine the first few 
thousand of such machines— and we 
found that among them there were 
only a few distinct kinds of behaviors. 
Some of them simply stopped with- 
out accomplishing anything. Many of 
the others just erased their input data 
and did nothing else. Most of the re- 
mainder quickly got trapped in circles, 
senselessly repeating the same steps 
over again. There were only a few left 
that did anything interesting at all— 
and these were all essentially the 
same: Each of them performed a 
counting operation that repeatedly in- 
creased by one the length of a string 
of symbols. In honor of their ability 
to do what resembles a fragment of 
simple arithmetic, let's call these A- 
machines. Let's think of this exploration 
as exposing parts of some infinite 

{continued) 



128 BYTE • APRIL 1985 




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| Gold Hill Computers 
163 Harvard Street 
Cambridge, MA 02139 



Bl-85 



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Name 
Title 



Department 



Organization 



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Today's Date 



Type of computer 

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T5 



COMMUNICATION 



"universe of possible computational 
structures," Then this tiny fragment of 
evidence suggests that such a 
universe may look something like 
figure 1. 

The Xs represent those useless pro- 
cesses that scarcely do anything at all. 
while the As represent those little 
counting machines, which in effect are 
all identical. Little processes like 
these, inside our minds, could be 
seeds of our more mature ideas 
about arithmetic. My point is that it 
seems inevitable that somewhere in 
a growing mind some A-machines 
must come to be. 

Now, possibly, there are some other 
really different ways to count. So there 
may appear much later some of what 
we represent as B~machines, which are 
processes that act in ways that are 
similar but not identical to the ways 
A-machines behave. But our experi- 
ment hints that even the simplest 
possible B-machine will be so much 
more complicated that it is unlikely 
any brain would discover one before 
it first found many A-machines. 

I think of this little thought experi- 
ment as resembling an abstract ver- 
sion of those first experiments in 
which Stanley Miller and Harold Urey 
set out to explore with real chemicals 
the simplest combinations of consti- 
tuents. They started with a few ele- 
ments like hydrogen, oxygen, nitro- 
gen, carbon, and phosphorus and 
found that those chemicals react first 
to make simple molecules and then 
go on to form peptides, sugars, 
nucleotides, and whatnot. Of course, 
we would have to wait much, much 
longer before the appearance of 
tigers, woodpeckers, or Andro- 
medans. 

A Real-Life Episode— Once, while 1 
was still a child in school, I heard that 
minus times minus is plus. How strange 
it seemed that negatives could cancel 
out— as though two wrongs could 
make a right, or "this statement lies" 
could be a truth. I wondered if there 
could be something else, still like 
arithmetic but having yet another 
sign. Why not make up some number 
things, I thought, that go not just two 
ways, but three? I searched for days, 



making up new little multiplication 
tables. Alas, each system ended either 
with impossible arithmetic (e.g., with 
one and two the same), with no signs 
at all, or with an extra sign. Eventual- 
ly, I gave up. If I had had the courage 
to persist, as Gauss did. I might have 
discovered the arithmetic of complex 
numbers or, as Pauli did, the arith- 
metic of spin matrices. But no one 
ever finds a three-signed imitation of 
arithmetic because, it seems, it sim- 
ply doesn't exist. 

Try, for example to make a new 
number system that's like the ordinary 
one except that it skips some 
number— say, 4. It just won't work. 
Everything will go wrong. You'll have 
to decide what 2 plus 2 is. If you say 
that this is 5, then 5 will have to be 
an even number, and so also must 7 
and 9. Then, what's 5 plus 5? Is it 8. 
or 9, or 10? You'll find that to make 
the new system at all like arithmetic 
you'll have to change the properties 
of all the other numbers. Then, when 
you're done, you'll find that you have 
changed only those numbers' names 
and not their properties at all. 

Similarly, you could try to make two 
different numbers be the same— say, 
139 and 145. But then, to make sub- 
traction work, you'll have to make 6 
the same as and 4 plus 5 equal to 
3. Suddenly, you'll find that the sum 
of two positive numbers is smaller 
than either of them— and that scarce- 



ly resembles arithmetic at all. (In fact, 
this leads to modular arithmetic, which 
has a certain usefulness in abstract 
mathematics but is worse than use- 
less for keeping track of real things.) 
And so it goes. 

There is just no way to take a single 
number out or put another one in. 
Nor can you change a single product, 
sum, or prime. 

What gives arithmetic this stark and 
singular rigidity? You cannot make the 
smallest hole in it or make it stretch 
or bend the slightest bit. You have to 
take it as it stands, the whole thing, 
all or nothing, unchangeable, because 
it's isolated as an island in that 
universe of processes. That selfsame 
A-machine exists, immutably com- 
plete, as part of every other process 
that can generate an endless chain of 
different things. 

1 sometimes wonder if it's danger- 
ous to make our children dwell so 
long on arithmetic since, when seen 
this way, it leads to such a singularly 
barren world. True, some children find 
in it a universe of different things to 
do. Most children, though, just find it 
dull—a source of endless rote and 
pointless pain; it's like the tedium of 
working clay too cold to mold into any 
other shape. 

From all this, I conclude that any en- 
tity who searches through the sim- 
plest processes will soon find frag- 

[continued] 



X x 
XXX 

Ax x A x 

x x A \ 

xx x x x A 

x x x A x / \ 

x A xx xx/xx \ xx 

X x /x X X XX x /x xxx\ x 
xxAx x xxAxxAx 

X Ax X X X A X XXX XX X / \ xxxx 

XX A XX XXXX XXX XX A X A X X 

X XXXAXXX XXX XXX XXX X / \xx XXX XXX 




Figure I: A universe of possible computational structures. 



APRIL 1985 • BYTE 



131 



Inquiry 362 



Pascal and C 

Programmers 



Your programs can 
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MaitwCord VISA* 



COMMUNICATION 



ments that do not merely resemble 
arithmetic but are arithmetic. It is not 
a matter of inventiveness or imagina- 
tion, only a fact about the geography 
of the universe of computation, a 
world far more constrained than that 
of real things. 

Thesis: All processes or formalisms 
that resemble arithmetic are either 
identical to it or else unthinkably com- 
plicated. This is why we can commu- 
nicate perfectly about numbers. 

What has this to do with aliens? 
Only that they too must have evolved 
by searching through some universe 
of possible processes, and any evolu- 
tionary process must first consider 
relatively simple systems and thus 
discover the same isolated islands of 
efficiency. 

Finally, we ought to ask why pro- 
cesses occur that way without some 
similar ones nearby? It is hard to for- 
mulate this precisely, because the 
meaning of similar depends on what 
you want to use it for. One way to ex- 
plain it is to point out that a small set 
of rules can generate a vast world of 
implications and consequences. But 
there is no converse because usually 
a small set of rules can't describe a 
large and complex thing. This is sim- 
ply a matter of arithmetic: There just 
aren't enough small sets of rules to go 
around! And that explains why we 
cannot take some set of rules, use it 
to generate a universe of conse- 
quences, make a few changes in that 
universe, and then describe that end 
result, again in terms of only a few 
rules. Now, that altered universe has 
become one of miracles, not of laws. 
There are not enough small sets of 
rules to produce the effect of con- 
tinuity. 

Causes and Clauses 

An alien mind would probably be en- 
tirely different from ours if how we 
think were just an evolutionary acci- 
dent. And then, communication 
would likely not be feasible. But al- 
though every evolution is composed 
of many accidents, each one tends to 
first try relatively simple ways at every 
stage, Since we're the first on earth to 



develop complex languages, and 
since these languages probably 
employ many relatively simple prin- 
ciples, it is likely that alien species will 
share many of these, I propose this 
in a form so strong that it may seem 
entirely preposterous at first; I believe 
that many aspects of our language/ 
grammar forms may be almost in- 
escapable. 

Why do we say things like "ft soon 
will start to rain?" Why must we always 
postulate some agent-cause even 
when there is no actor on the scene? 
It doesn't matter if we're right or 
wrong; we'll find a cause or imagine 
one. 1 claim we seek some cause for 
every difference, move, or change. 
Sometimes our language syntax 
forces this on us, but I claim it is not 
merely a matter of verbal form; it 
stems from deeper causes in the ways 
we think. My guess is that even before 
our ancestors began to speak, they 
first developed special brain ma- 
chinery for representing objects, dif- 
ferences, and causes, and our lan- 
guage/grammar later reflected these. 
Specifically, I suspect that many of our 
thought processes are based on using 
the following kinds of mental symbol 
representations: 

Object-symbols representing things, 
ideas, or processes— In languages, 
they often correspond to nouns. Our 
minds tend to describe every situa- 
tion, real or mental, in terms of 
separate object-things and the rela- 
tions between them. 
Difference-symbols representing dif- 
ferences between, or changes in, 
objects— In languages, they often cor- 
respond to verbs. When any object 
undergoes a change or two objects 
are compared, the mind ascribes 
some differences to them. 
Cause-symbols— When any difference 
is conceived, the mind finds a cause 
for it, a something that is held respon- 
sible. And we use a clever mental trick 
to represent causes in much the same 
ways that we represent objects. 
Cla use-structures— For describing 
complicated situations, we have a 
trick that lets us treat any expression 

{continued) 



132 B YTE • APRIL 1985 



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Inquiry 248 



M>i#7r//v M>«#7/erra 



Martin Marietta Data Systems 

APRIL 1985 -BYTE 



133 



COMMUNICATION 



or description, however complicated, 
as though it were a single component 
of another description. In languages, 
this corresponds to using embedded 
phrases and clauses. 

It is that final self-embedding trick 
of representing prior thoughts as 
things that gives our minds their awe- 
some power. For this permits us to re- 
use the same brain machinery over 
and over again, at each step replac- 
ing an entire conceptualization by a 
compact symbol. That way, we can 
build up gigantic structures of ideas 
as easily as our children build great 
bridges and towers from simple 
separate blocks. That way, we can 
build new ideas from old ones— and 
that is what enables us to think. This 
applies to our computers as well. 

This must be why our languages 
also have structures that we can re- 
use: Our thoughts themselves must 
use the same machinery repeatedly. 
That's how our thoughts extend them- 
selves to infinite variety. And. unless 
aliens do that too, they cannot turn 
their thoughts to the prior products 
of their thoughts. Without this trick of 
turning symbols on themselves, you 
can't have general intelligence, 
however excellent your repertoire of 
other skills may be. 

Critic: You might as well argue that the 
aliens will speak English if you claim 
they too use nouns and verbs and 
compound embedded sentences. But 
what if they don't think in terms of ob- 
jects and actions at all? 

1 don't think it's an accident that we 
think in terms of thing and cause. 
Whatever may occur, that form of rep- 
resentation leads us always to wonder 
who or what is responsible. And so. 
this evolutionary trick leads us to 
search to find dependencies that help 
predict— and hence control— not just the 
world outside but also what may hap- 
pen in the mind. Perhaps it's also why 
we all grow up believing in a self: 
perhaps that "I" in "1 just had a good 
idea" stems from that same ma- 
chinery. Because if you are compelled 
to find something to cause the things 
you do, that something needs to have 



a name. You call it "me." I call it 
"you" 

Critic: But what's so great about 
dependencies? Why can't some aliens 
perceive entire scenes as wholes in- 
stead of breaking them down into 
those clumsy parts? Why not, instead, 
see what there really is, holistically— 
a steady flow of flux in space in time, 
instead of arbitrary form-filled mind- 
made fragments of approximations to 
reality? 

It surely is a healthy tendency to yearn 
for better ways to see the world. But 
worshipping as-yet-undiscovered 
transcendental schemes can blind us 
to the power we draw from our usual 
ways of separating things. Each 
animal must pay a corresponding 
price in energy and nourishment for 
each machine it carries in its brain, 
lust as clause structure in language 
lets us focus our entire word machine 
on each part of a description, our con- 
cept of seeing separate things lets us 
factor situations into parts and then 
apply our whole mind machine to 
each part of the problem. Enthusiasts 
of holism have never understood the 
hidden cost a mind would have to pay 
to "see everything at once." We'd 
never be able to see anything clearly 
at all. 

There have been many speculations 
on how brains might use something 
like holograms for memories. But on 
one side there is no evidence for this; 
on the other there are few advantages 
to it. Holograms store no more infor- 
mation than other methods, and com- 
puter scientists know other, better 
ways to add redundancy to memory 
to make it robust and injury resistant. 
It is true that holograms can simplify 
certain kinds of recognitions, for in- 
stance, deciding whether a picture 
contains copies of some specific 
other picture. But that also makes it 
much more difficult to make most 
other kinds of decisions, to say 
whether a picture contains two sub- 
pictures that share some specified 
relationship. In fact, a hologram may 
be almost the worst possible way to 
represent relations among the things 
it represents, because memory and 



learning are useful only when they in- 
form us about relations that are at 
least partially predictable. We do not 
want our memories to give equal 
weights to every arbitrary feature of 
a situation. If a scene contains 50 
features, you don't want to equally 
consider all the quadrillion possible 
subsets of those features. And so we 
need some methods for isolating and 
grouping that can emphasize the 
most usefully predictable subsets. In 
short, without the additional con- 
straints on relations between features, 
which result in the concept of an ob- 
ject, we'd simply never see the same 
thing twice. Then we'd have no way to 
learn from our experience. No knowl- 
edge could accumulate. 

Causes and Goals 

How does having memory help- 
when no two problems are ever quite 
the same in all respects? Our past ex- 
perience would seem to have no 
relevance unless we had some ways 
to see which aspects of the world re- 
main the same, while others change. 
This is why knowledge cannot have 
much use unless expressed in terms 
of relations between predictable fea- 
tures and the actions that we can take. 
But given these it then may become 
possible to predict which actions 
might cause undesirable features to 
disappear. 

To say that "y happened because of 
x" is, in effect, to say that x can help 
you to predict which actions can lead 
to y, It helps to control its environ- 
ment if an animal can find such 
causes— fragments of predictability that 
work better than chance. But such 
predictions aren't useful when too 
many small effects add up. What are 
causes anyway? The very concept of 
a cause involves a certain element of 
style: A causal explanation must be 
brief. Unless an explanation is com- 
pact, we cannot use it to predict. We 
would agree that x is a cause of y if 
we see that y depends much more on 
x than on most other things. But we 
wouldn't call x a cause if it were a 
discourse that carried on and on, 
mentioning everything else in the 

(continued) 



134 BYT! 



APRIL 198S 



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Inquiry 40 

*Contact BASF for warranty details. 



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BASF 

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Inquiry 288 




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FUJI (10) 18 

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IBM (10) 22 

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COMMUNICATION 



whole world and never coming to any 
point. This applies to objects too. 

There can't be any objects, things, or 
causes in worlds where everything 
that happens depends, more or less 
equally, on everything else that 
happens. 

It makes no sense to talk about a 
thing in such a world, because our very 
notion of a thing assumes some con- 
stellation of properties that stays the 
same or changes ways we can predict, 
when other things around it change. 
When you move an object, its location 
changes— but not its color, weight, 
material, size, or shape. How conve- 
nient that our world lets us change a 
thing's place and still leave so many 
other properties unchanged. If this 
were not the case, the number of 
combinations to keep track of would 
grow exponentially with the number 
of features we perceive and we would 
have no sense of what causes things to 
happen. 

To deal with something complicated, 
you must find a way to describe it in 
terms of substructures within which 
the effects of actions tend to be 
localized. Tb know the cause of a 
phenomenon is to know, at least in 
principle, what can change or control 
it without changing everything else. 
This is useful when it enables us to 
change one thing without making 
other things worse. 

For a mind to discover causes in its 
world, it must have sensors that 
detect changes that are predictably 
related to the actions it can take. For- 
tunately, evolution tends automatical- 
ly to select just such matched sets of 
sensors and effectors, because in vir- 
tually any environment an animal's 
survival is enhanced if its actions are 
based on good predictions. So we can 
expect evolutionary processes to ac- 
cumulate mechanisms that reflect the 
causal laws that operate in their en- 
vironments. And it would seem that 
the most powerful methods are those 
that let you make predictions about 
the effects of contemplated action 
chains, that is, the ability to make 
plans. 



Problems seem hard when their 
solutions aren't obvious. The most 
general way we know to solve prob- 
lems is to set up systems that have 
some way to make "progress toward 
a goal." In the late 1950s, A. Newell 
and H. A. Simon worked out a theory 
of what they called the "General Prob- 
lem Solver." This is a theory of how 
to reach a goal by making progress— 
finding actions that can replace each 
problem that has a high-level difficulty by 
other problems, each of which has a 
lower-level difficulty. No one can 
prove that all intelligent problem 
solvers, however alien, must use this 
selfsame principle. But until we find 
another, comparably general idea— 
and none is on our horizon— it is hard 
to imagine how an intelligence could 
evolve without exploiting some such 
idea of goal. 

Reliable Communication 

Before we ask how aliens communi- 
cate, we ought to ask how humans 
can. Is there ever a word that means 
the same to any two of us? Everyone 
must have wondered once, "Could 
two persons have different meanings 
for every word, yet never sense that 
anything is wrong?" What if each thing 
that's green or blue to me is blue and 
green to you? The sparseness theory 
claims that we need have no fear of 
that, at least for technical concepts, 
since one of the two outwardly in- 
distinguishable meanings would prob- 
ably be vastly more complicated than 
the other and would never have been 
conceived in the first place. Sparse- 
ness means we can trust one another. 
We know very little of where that 
idea might lead because we know so 
little about how sparseness isolates 
any particular concept. But the 
general idea does seem to support 
the mathematical and physical intui- 
tions proposed by Hans Freudenthal 
in LINCOS, his book on alien commu- 
nication, perhaps even in regard to 
the miniature models he suggests for 
discussing social and administrative 
subjects. There is one problem 
though: Introspection is a poor guide 
for guessing which of our common- 

{continued} 



136 B YTE • APRIL 1985 



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COMMUNICATION 



sense concepts are really simple, 
because many things we find easy to 
do use brain machines whose com- 
plexity we cannot sense. For exam- 
ple, we find it easy to stand on two 
feet, but some aliens might find that 
quite astonishing. 

What other ideas are likely to be 
universal in the sense of being islands 
in that sea of possible ideas? Surely 
the mathematical notions of utility, 
linear approximation, probability, and 
the simplest program-like processes 
are. These could serve to communi- 
cate much about trade and com- 
merce, basic facts of biology, and 
even many principles of mental life— 
e.g., about objects, goals, and mem- 
ories. At some point, though, sparse- 
ness must fail, because things that are 
more complicated will have all kinds 
of variations and alternatives, and 



communication will encounter ob- 
stacles of every sort. 

Therefore 

There is little more that I can say to- 
day with any scientific certitude. 
Tomorrow there could be more, 
perhaps because of soon-to-come 
gains in computational power that 
could let us explore a little further 
into the mysterious ocean of all pos- 
sible simple machines. There we 
might find a few more ideas isolated 
enough to share with other minds. 
Such explorations also might tell us 
more about the origin of life itself by 
showing us the simplest schemes that 
could support the simplest forms of 
evolutionary search. ■ 

BIBLIOGRAPHY 

Ernst, G., and Allen Newell. GPS: A Case 



Study in Generality and Problem Solving. New 
York: Academic Press, 1969. 
Freudenthal, Hans. UNCOS: Design of a 
Language for Cosmic Intercourse. Amsterdam; 
North-Holland. 1960. 
Lenat, Douglas. 'The Nature of Heuristics," 
Artificial Intelligence, vol. 19, 1982. 
TUring, Alan. "On Computable Numbers, 
With an Application to the Entscheidungs- 
problem," Proceedings of the London 
Mathematical Society, vol. 2, 1937; reprinted 
in Martin Davis (ed.), The Undecidable. New 
York: Raven Press, 1965. 

ACKNOWLEDGMENT 
This article is an adapted version of a 
paper by Marvin Minsky in Extraterrestrials: 
Science and Alien Intelligence, edited by 
Edward Regis Jr. and published by Cam- 
bridge University Press. Copyright March 
13, 1984, revised December 10, 1984. The 
book will be available in the summer of 
1985. Reprinted with permission of the 
editor and Cambridge University Press. 



A Glossary 
of Artificial-Intelligence TErms 



And, Or, and Stream Paral- 
lelism: different techniques for im- 
plementing parallel operations, 
based on and, or, and pipelined ex- 
ecution hierarchies. 

Bags: formal mathematical objects 
that differ from sets in that they 
allow duplicate items. 

Blackboard: used in systems 
composed of independent 
modules as a means of communi- 
cation. The blackboard is a com- 
mon area of memory containing 
system-state data that all modules 
can access. 

Frame: a knowledge structure (or 
database) used to describe the at- 
tributes that an object possesses, 
arranged in a "slot and filler" for- 
mat. Each slot and its contents 
carry information about a par- 
ticular aspect of the object. 

Grain Size: when used in conjunc- 
tion with parallel processing, grain 
size refers to the complexity of the 



code chunks allocated to each pro- 
cessor. For example, if processor A 
is assigned to perform an addition 
operation while processor B is 
assigned to perform a sort opera- 
tion, the grain size of the code 
assigned to processor A is smaller 
than that assigned to processor B. 

Heuristic: a technique that im- 
proves the efficiency of a problem- 
solving process, even though its 
use cannot be strictly justified. In 
AI, heuristics are typically used to 
reduce the time required to solve 
extremely complex search prob- 
lems. 

Knowledge Engineer: an AI pro- 
grammer who constructs expert 

systems. 

Predicates and Demons: a predi- 
cate is a type of function that tests 
for some condition involving its 
arguments. A demon is a proce- 
dure that activates automatically in 
response to recognizing a prede- 
fined state. 



Script: a frame-like knowledge 
structure used to represent related 
sequences of events. The slots in 
a script contain information con- 
cerning an event (where the event 
occurs, people involved, objects 
manipulated, etc.), and the events 
are linked in a causal chain. 

Semantic Net: a graph of nodes 
and connecting links; the nodes 
represent objects, and the links 
represent relationships. A family 
tree is a good example of a seman- 
tic net. 

Tagged Memory Architecture: in 

AI applications, tagged memory ar- 
chitectures use part of each mem- 
ory word to convey information 
about the data stored in the re- 
maining bits of that word, includ- 
ing the data type and format. 

Unification: a pattern-matching 
method; the result of a unification 
is the assignment of values to the 
variables of two patterns so that 
both patterns become identical. 



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ARTIFICIAL INTELLIGENCE 



THE QUEST 

TO UNDERSTAND 

THINKING 

by Roger Schank and Larry Hunter 



It begins not with complex issues 
but with the most trivial of processes 



ARTIFICIAL INTELLIGENCE, or AI, 
takes as its subject matter some of the 
most daunting questions of our ex- 
istence. What is the nature of mind? 
What are we doing when we are think- 
ing, feeling, seeing, or understanding? 
Is it possible to comprehend how our 
minds really work? These questions 
have been asked for thousands of 
years, but we've made little tangible 
progress at answering them. 

AI offers a new tool for those pur- 
suing the quest: the computer. As 
anyone who has used one can attest, 
computers often create more prob- 
lems than they solve. But for probing 
the issues of mind and thought, that 
is just what we need. 

The fundamental use of computers 
in helping us understand cognition is 
to provide a testbed for our ideas 
about what the mind does. Theories 
of mind often take the form of pro- 
cess descriptions. For example, a 
theory of question answering might 
claim that people first translate a 
question into an internal representa- 
tion, use that representation as an 
index into memory, translate the re- 
called memory into an appropriate 



form for an answer, and then generate 
the words to communicate it. (This ex- 
ample is offered not as a real theory 
of question answering but as an ex- 
ample of what a process theory of 
mind might look like.) 

Process theories seem to be a good 
way of describing what might go on 
inside the brain. One problem with 
them, however, is that all too often 
what looks like a good description 
really isn't specific enough to make 
the theory clear. "Use the represen- 
tation as an index into memory" isn't 
a good explanation of the processes 
behind remembering a fact. How are 
facts recalled? How is the memory 
organized? What happens when 
memory gets very large? What if a fact 
isn't directly encoded in memory but 
can be inferred from something that 
is? A researcher trying to write a pro- 
gram that embodies the above sim- 
plistic theory would run into all of 
these problems and more. That's why 
we need to write programs. Program- 
ming forces us to be explicit, and be- 
ing explicit forces us to confront the 
problems with our theories. 

Not long ago, AI researchers like 



ourselves focused on what they con- 
sidered to be manifestations of highly 
intelligent behavior; playing chess, 
proving mathematical theorems, solv- 
ing complex logical puzzles, and the 
like. Many AI researchers devoted a 
lot of energy to these projects and 
found powerful computational tech- 
niques for accomplishing such "intel- 
ligent" tasks. But we discovered that 
the techniques we developed are not 
the same ones that people actually 
use to perform these tasks, and we 
have instead begun to concentrate on 
tasks that almost any adult finds 
trivial: using language, showing com- 
mon sense, learning from past expe- 
riences. 

Language 

We began studying these "trivial" 
tasks by trying to write programs that 

[continued) 
Roger Schank is chairman of the computer 
science department at Yale University. Larry 
Hunter is a graduate student in computer 
science at Yale. Both authors can be reached 
at the Yale University Artificial Intelligence 
Laboratory, 10 Hillhouse Ave., New Haven, 
CT 06520. 



APRIL 1985 'BYTE 143 



THINKING 



People understand 
a great deal more 
than the lexical content 
of an utterance. 



could use English (or other natural 
languages) in a useful way. We wanted 
such programs to be able to under- 
stand the written word well enough to 
summarize it, translate it into another 
language, or answer questions about 
it. We were immediately confronted 
with the fact that people understand 
a great deal more than just the im- 
mediate lexical content of an ut- 
terance. For example, most people 
would agree that the sentence "John 
bought a new car" contains a refer- 
ence to money even though the word 
"money" does not appear in the 
sentence. Any program that under- 
stands that sentence would have to be 
able to answer "Yes" to the question 
"Did John spend money 9 " 

How could a program know that? 
One approach might be to associate 
"money" with the word "bought," 
claiming that "buy" means "trade 
money for." This method uses the 
meanings of the various words in the 
sentence to build up a representation 
of the meaning of the whole sentence 
That is more or less the right ap- 
proach, but it has some problems. For 
one, words are ambiguous, and the in- 
ferences we make about their mean- 
ings can easily be wrong. "Buy," for 
example, doesn't always mean money 
changes hands, as in: ")ohn bought 
Mary's argument." Ambiguity is so 
widespread that any program dealing 
with natural language must have 
powerful methods for handling it. 

Another problem is that often 
underlying meanings do not come 
from the definitions of any particular 
word. Consider the following story: 
"lohn went to a restaurant. He 
ordered a sandwich. The waiter 
brought it quickly, so he left a large 
tip" The meaning of this story ob- 
viously includes the fact that )ohn ate 



the sandwich and paid for it. However, 
those actions are not implicit in any 
particular word in the story. How 
might a computer program infer 
them? It would have to know about 
what goes on in restaurants. A person 
could also conclude that lohn prob- 
ably looked at a menu, that he sat at 
a table, that a cook made the sand- 
wich, and so on. The program needs 
to be able to fill in the unmentioned 
gaps in a text with information about 
the events being described. 

There is a solution to both prob- 
lems: The program must be constant- 
ly generating expectations about what 
will happen next. Ambiguity is rarely 
noticed by human speakers because 
the context makes clear which mean- 
ing is correct. For a program to be 
able to resolve ambiguity it must 
build up a "context" as well. In other 
words, the program must have some 
idea of what will happen next, based 
on what has happened previously and 
what it already knows about these 
kinds of situations. Expectations are 
very helpful in resolving ambiguity; 
the expected sense of an ambiguous 
word is the one that should be as- 
sumed. The expectations set up by 
"The bartender poured scotch on . . ." 
makes it easy to use the proper sense 
of "the rocks" 

Expectations also help fill in the 
gaps in a story They commonly come 
in bunches or packages. When we hear 
about a restaurant, we expect to hear 
about a variety of objects, events, and 
people. There should be a menu, the 
patron should look at the menu, pick 
something, tell the order to a waiter 
or waitress, wait for a while, be served, 
eat the food, have the table cleared, 
get a check, pay the check, leave a tip, 
and depart. As is obvious from this 
example, expectation packages can 
be temporally ordered, which makes 
it possible to infer that "[ohn ate his 
sandwich" in the earlier example. 
When an expectation is satisfied, the 
program can infer that the expecta- 
tions temporally prior to it are prob- 
ably also satisfied. People know about 
common sequences of actions in the 
world and use that knowledge to gen- 
erate expectations. There is no way to 



understand language without know- 
ing something about the subject mat- 
ter under discussion. 

To build programs that test these 
ideas, we had to figure out what kinds 
of expectations exist and specifically 
how they are used. First, we looked 
to human behavior to guide us. Peo- 
ple constantly generate expectations 
at many different levels of specificity 
We have expectations about what syl- 
lable sounds are likely to be heard 
next that help us resolve ambiguous 
sounds into words. We have lexical ex- 
pectations about what words or 
classes of words will come next. We 
have expectations of events that are 
likely to occur. We also have a variety 
of expectations about other things, 
like the kinds of goals that various 
people may have, plans and counter- 
plans involved in pursuing those 
goals, and emotional reactions to 
various events. 

Then we thought about how a pro- 
gram might handle this. In some 
sense, every natural-language parser 
uses expectations. The difference be- 
tween a traditional, strictly syntactic 
parser and a more conceptual parser 
is the source of its expectations. A 
syntactic parser uses only knowledge 
about grammar. A conceptual parser 
uses information from many sources, 
grammatical and otherwise. While a 
traditional parser sees syntactic 
analysis as a preliminary process for 
other analyses, a conceptual parser 
sees syntax as only one of many 
sources of information used simulta- 
neously to understand text. 

Many of the low-level expectations 
of our parsers come from the vocab- 
ulary used to represent meaning. 
Some of our programs have used con- 
ceptual dependency (CD) to represent 
meanings (see reference 1). The basic 
CD form has slots for an action, an ac- 
tor, an object, and a directional com- 
ponent (from or to). Each CD action 
has associated semantic constraints 
on the kinds of entities that can fill its 
slots. For example, the CD action in- 
gest requires that its object be edible 
and its actor be alive. When any word 
that refers to "ingest" appears in a 

{continued} 



144 B YTE • APRIL 1985 






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Inquiry 379 



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What every Apple owner 
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146 BYTE • APRIL 1985 



•^ 



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Inquiry 326 

Quark and Word Juggler are trademarks of Quark Incorporated. Apple is a 
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Ask about our specially- priced educational version. 



[1985J 



t Barbara Kasten 



THINKING 



text, expectations are generated to 
hear about an edible object (general- 
ly after the word meaning "ingest") 
and a living actor (generally before 
"ingest"). Notice that the expectations 
generated are both semantic (predict- 
ing a word or meaning) and syntactic 
(predicting where the word might be 
found). Of course, even the CD action 
may be ambiguous. One way to clear 
up the ambiguity in such cases is to 
generate the expectations from both 
possible meanings and pick the action 
whose expectations are met by the re- 
maining words in the story. This tech- 
nique could be used to clarify the 
meaning of "buy" in the earlier exam- 
ple; "buy" would generate two sets of 
expectations, one predicting a valu- 
able object and the other predicting 
an opinion. When one expectation set 
was satisfied, the program could de- 
activate the other. 

There are many other ways to clear 
up ambiguities. More complex expec- 
tation schemes can provide better in- 
formation. Consider the restaurant 
story above. The sentence The waiter 
brought it quickly, so he left a large 
tip" has an ambiguous pronoun, "he." 
Standard rules for pronoun reference 
fail here; sex and number don't dif- 
ferentiate, and "he" does not refer to 
the most recent agreeing antecedent, 
"waiter." The only way to clarify the 
meaning of this pronoun is by the ex- 
pectation that patrons leave tips for 
servers. You might try associating this 
information with the appropriate 
meaning for the word "tip," but patron 
and server are not just semantic re- 
strictions on slot fillers, lohn might be 
a patron in this episode, but he might 
act as a server in some other situa- 
tion. The patron/server/tip expectation 
and the identification of John as a 
patron must come from a package of 
expectations about restaurants. 

When we began to use packages of 
expectations in programs, we dis- 
covered a few things about packages. 
First, any story will refer to many 
packages, and the packages can relate 
to each other in many different ways. 
Packages can be grouped together 
themselves (date = drive, restaurant, 
drive, movie, drive) or can fill slots in 



some other package (the "pay" slot 
of restaurant might be filled by "wash 
dishes"). They can occur at the same 
time (eating and taking an airplane) or 
be incompatible (driving an auto- 
mobile and taking an airplane). Pack- 
ages can also have word senses as- 
sociated with them. In the restaurant 
package, "tip" is more likely to mean 
"money" than "end point." This kind 
of associated lexicon doesn't solve 
the problem of ambiguity, but it is a 
helpful tool. 

We also ran into some problems 
with packages. How could a program 
figure out which package to use at any 
given time? It is reasonable to add ac- 
tivation conditions to a package that 
specify the situations in which that 
package might be relevant. Early pro- 
grams just looked at each package to 
see if its conditions had been met. As 
the number of packages increased, 
their organization had to improve. We 



needed some way of finding the right 
set of expectations at the right mo- 
ment, without looking at every pack- 
age. As we built programs that used 
packaged expectations and gave 
them real stories (taken verbatim from 
the UP1 newswire), we noticed that 
sometimes expectations failed. These 
failures were often very interesting 
events. We began working on ways to 
determine the difference between a 
failed expectation and an unresolved 
one that should be inferred. 

Another problem was picking what 
was to be a package and what wasn't. 
There are many things about eating at 
home that are like going to a restaurant. 
Do the expectations about eating at 
home come from the same package 
or a totally different one? How about 
eating in different restaurants? We 
needed a theory of how to organize 
and find groups of expectations. 

{continued) 



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APRIL 1985 "BYTE 147 



Inquir> 69 



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148 B YTE • APRIL 1985 





THINKING 



Briefly, we began by looking at lan- 
guage. We wanted to generate a pro- 
gram that would read a few sentences 
and answer questions about them. We 
have found that, in order to do this, 
we need to build expectations about 
the subject matter of the text. Those 
expectations come from many diverse 
sources of knowledge and are bun- 
dled together into packages. We then 
have to consider what kinds of pack- 
ages there are and how we can 
organize and use them. What began 
as a study of language has turned into 
a study of knowledge and knowledge 
organization— in other words, a study 
of memory. 

Memory 

Where do predictions come from^ 
How do we know what to expect 
next? We use relevant previous expe- 
riences to help us understand. New- 
borns can't comprehend restaurant 
stories, and people who have worked 
in restaurants can read more into 
seemingly insignificant events. We en- 
code what we see in terms of what we 
have already experienced. That is why 
two people can see the same event 
and yet understand it very dif- 
ferently—they each bring different 
beliefs and expectations to bear. Our 
ability to understand a situation 
comes from our ability to compare it 
to relevant previous situations. The 
knowledge we gain from experi- 
ence—episodic memory— is the same 
knowledge we use to understand— 
semantic memory. 

How does this relate to our predic- 
tion packages? The first thing we 
noticed was that using packages 
might be an efficient way to re- 
member episodes. Instead of having 
to store every event in an experience, 
a program could just save a pointer 
to the prototype (restaurant, for exam- 
ple) along with those parts of the ex- 
perience that weren't part of the 
package (for example, the patron was 
John, the food was a sandwich, the tip 
was large). Memory need only register 
those parts of an episode that dif- 
ferentiate it from the prototype. Since 
packages contain what we expect in 
a situation, they are effectively pro- 



totypes; hence, they can serve to 
organize memory of events. Our pack- 
ages now have another role to play: 
They should accomplish the functions 
of event memory as well as provide 
the expectations that aid in under- 
standing. 

If packages are to function as mem- 
ory as well as processing structures, 
they have additional requirements. 
First and foremost, a memory system 
must be dynamic. The memory must 
be altered by its experiences. A 
memory system that fails to respond 
to new inputs and learn from its ex- 
periences is not very useful. A 
memory system that produces expec- 
tations must be able to respond to ex- 
pectation failures by reorganizing 
itself to provide better expectations 
in the future. Second, a memory sys- 
tem must be able to find what it 
knows. This may not seem very hard, 
but it is. The task of memory is to take 
a given event and find related events. 
But what constitutes a "related" 
event, and how do we know where to 
look for one? These two goals— re- 
membering and learning— drive our 
theorizing about the structure of 
memory. We need to understand how 
knowledge is structured and how it 
can change. 

We also have a powerful technique 
with which to investigate the structure 
of human memory: reminding. Re- 
minding is a ubiquitous phenom- 
enon; people are constantly re- 
minded of one thing by another. You 
can be reminded of an object, a per- 
son, or a situation. In the course of 
normal conversation, people are often 
reminded of previous events. During 
the mental processing of that conver- 
sation, some memory is activated to 
help understand the new input. The 
fact that one experience reminds us 
of another indicates that we are using 
the same structure to process one as 
to remember the other. By examining 
the process of reminding, we can ex- 
plore the structure of memory. 

Armed with our new conception of 
memory structures, let's return to our 
restaurant example. Suppose that 
when John received the bill, the waiter 

[continued} 




A modem that 

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9m 




© Lockheed-GETEX 1985 




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Inquiry 238 



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I 
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Inquiry 256 




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150 BYTE- APRIL 1985 



THINKING 



Common sense is 
knowing about a lot 
of things and using 
what you know in a 
variety of situations. 



had made an arithmetic error and 
charged him too much. John noticed 
this and complained. The waiter was 
apologetic and not only fixed the 
error but offered )ohn a free dessert. 
John— or any dynamic memory sys- 
tem trying to understand what is 
happening— should record this devia- 
tion from the expected routine If he 
were later to notice a similar error 
while buying auto parts, he might be 
reminded of his experience in the 
restaurant. He might then expect 
compensation from the store to make 
up for the mistake. How can an ex- 
perience in an auto-parts store remind 
you of an experience in a restaurant? 
There must be some memory struc- 
ture that is used to understand both 
experiences. In addition, by storing in- 
formation about expectation failure 
(and its results) in the shared struc- 
ture, we automatically make an appro- 
priate generalization. 

What does this tell us about the 
organization of memory? Surely not 
all the expectations are the same 
across these events; )ohn doesn't ex- 
pect to see a menu or be served a 
lobster dinner in the auto-parts store. 
But some expectations are indeed the 
same: He expects to find out what is 
available, to tell someone what he 
wants, to receive it, to get a bill for 
what he has ordered, and to pay the 
bill, Some major scenes happen in 
one event and not in the other; there 
is no equivalent to being directed to 
a table by a hostess in the auto-parts 
store. Also, the specifics added to the 
generalized scenes are different. For 
example, in an auto-parts store you 
find what you want by looking 
through fat catalogs of numbered 



parts sorted by model and year; in a 
restaurant, you look at the menu. 

We can draw several conclusions 
about memory structures. Packages 
are nested, that is, packages have sub- 
packages. In Al terminology, the pack- 
ages are called MOPs (for memory or- 
ganization packages), and the sub- 
packages, scenes. Scenes are 
shared— most appear in many MOPs. 
Examples of scenes might be pay and 
order. It is important to note here that 
there is no "correct" list of packages. 
The packages that any dynamic mem- 
ory system uses at any particular time 
depend on its own prior experiences. 
Furthermore, a MOP contains infor- 
mation about the specific details of its 
own scenes. These details are called 
colorations: for example, the restaurant 
MOP might color the pay scene by 
specifying the acceptable types of 
payment in a restaurant (cash, credit, 
dishwashing, etc.). 

The ability to share scenes provides 
a mechanism for making useful gen- 
eralizations. When there is an expec- 
tation failure and the source of the ex- 
pectation is part of a shared structure, 
the failure and any new expectations 
based on that failure are stored in that 
structure. When a similar situation oc- 
curs, even in a different package, the 
previous failure comes to mind (is re- 
minded) because it is stored in the 
shared scene. Then it can be used to 
help guide processing. A program 
using this system might learn to count 
its change in the auto-parts store after 
being shortchanged in the restaurant, 
since both use the pay scene. This 
combination of failure-driven learning 
and shared memory structures is 
quite powerful. Expectation failure 
can also be used to build new MOPs 
from old ones by changing the colora- 
tions or the order of scenes (for ex- 
ample, in fast-food restaurants, you 
pay before you eat). 

Many more kinds of memory and 
processing structures are used in our 
Al theories and programs than we can 
describe here, but the basic require- 
ments of a useful memory organiza- 
tion should be clear. (For more infor- 
mation, see references 2 and 3.) What 

[continued) 



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THINKING 



may not be clear is how important 
memory and its organization are to 
nearly all cognitive activity. Getting 
just the right piece of knowledge at 
the right moment from our huge and 
constantly changing memory is not 
only crucial for language understand- 
ing but crucial for exhibiting common 
sense (which is really just knowing 
about a lot of things and being able 
to use what you know in a variety of 
situations), for applying expert knowl- 
edge for writing interesting stories, 
and for accomplishing a host of other 
tasks. Being able to learn from expe- 
rience and apply that knowledge in 
relevant situations is an important 
step toward actual intelligence. 

What Is AI? 

The term "artificial intelligence" has 
been much abused of late, and we 
would like to try to clarify what we 
mean by it. Programs that manifest 
theories of knowledge do interesting, 
sometimes even impressive feats. But 
many programs that are not attempt- 
ing to model cognition also do im- 
pressive things. The public perception 
of AI has focused on the artificial. 
Computers are indeed doing things 
we never imagined machines could 
do. Computer scientists and engineers 
are constantly expanding the useful- 
ness and power of their machines. 
That is important science and engi- 
neering, but it is not AI. AI focuses on 
intelligence, something that remains 
mysterious and elusive. Most good AI 
programs aren't terribly useful, and 
many very useful, "smart" programs 
aren't AI at all. If this distinction were 
understood, we could avoid a lot of 
confusion and disappointment. 

So-called expert systems are a case 
in point. These programs, more ac- 
curately dubbed "rule-based," do not 
attempt to reason the way a human 
expert would. They often do very 
useful tasks, and that's great, but they 
are not model theories of intelligence. 
A human expert is not someone who 
is just following the rules. He has the 
experience to know when he is seeing 
an exceptional case and he can recall 
relevant past cases to help him figure 

[continued) 



152 B YTE • APRIL 1985 



Inquiry 373 




Resource Technology — What's it all about? 

IT'S ABOUT TIME! 

.and Time is relative. In business, time is profitability! 



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husincss, however, the hofflom line i* directly proportionate 
h» the quality of, and the time Consumed by, the tools 
employed - (see digital examples). 




\ 



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THINKING 



out what to do. AI theories of expert 
behavior must describe how an ex- 
pert knows when something doesn't 
fit his general rules and what to do 
about it. AI theories need to account 
for how experts change and add to 
the rules they use, based on the suc- 
cess or failure of those rules. 

Artificial intelligence is a much more 
basic science than is popularly be- 
lieved. Many of our best AI ideas re- 
quire a great deal of work before they 
can become useful applications. And 
when an AI idea is turned into a 
useful system, in some sense it isn't 
AI anymore. The construction of such 
a system requires all kinds of non-AI 
programming effort— to make the idea 
work in a real environment, on real 
computers, in some useful way. Such 
a system is made possible by the AI 
idea, but the program's merit comes 
from its functionality, not its heritage. 
The fact that a program is based on 
an AI idea is no way to judge its func- 
tionality. 

Are there any applications of AI? 
We think so. If we are gaining insights 
into how people think, then our find- 
ings should help people think better. 
Perhaps AI's most important applica- 
tions will not be the programs that we 
write but the newfound ability to 
understand how people think. As we 
find out more about how people read, 
understand, and create, we may be 
able to help them do those things bet- 
ter. Perhaps AI's most promising ap- 
plications are in education— helping 
to teach people how to read, remem- 
ber, and think based on a fundamen- 
tal knowledge of those processes. 

Let's consider the problem of teach- 
ing children— or adults— to read. In 
trying to write programs that can 
read, we have learned a great deal 
about the reading process. Perhaps 
we can transfer some of this into im- 
proved techniques for teaching read- 
ing. Of course, this is not always a 
straightforward task, but we believe it 
is possible. Expectations play a cen- 
tral role in understanding text. As 
children build up expectations about 
words and stories, they become bet- 
ter readers. Language ability is strong- 
ly tied to knowing the content of the 



material, so the books children read 
should relate to what they know. We 
may be able to write better reading 
textbooks by using expectation pack- 
ages that children know about. We 
can write textbooks that encourage 
them to use their knowledge to fill in 
the details behind the text, to make 
inferences. Since AI has focused on 
language for most of its existence, it 
has a lot to contribute to reading 
education. But that's not all AI has to 
offer; its promise extends throughout 
education and beyond. AI should 
eventually provide insights into how 
to learn and remember better, how to 
improve explanatory faculties, and 
even how to extend creativity. 

Artificial intelligence is part of the 
grand attempt to understand thinking. 
We believe it is making important con- 
tributions to that endeavor, and that 
is the goal of our science. The pro- 
grams we write are experiments, not 



results. Our interest is intelligence, not 
artifact. As we make progress, our 
results may prepare the way for the 
automated companions that could 
become an indispensable part of 
everyday life. These will not be our 
real results, though. The real results 
will be a new kind of understanding 
of ourselves, an understanding that is 
ultimately much more valuable than 
any program. ■ 

REFERENCES 

1. Schank, Roger C. Conceptual Information 
Processing. Amsterdam: North-Holland, 
1975. 

2. Schank, Roger C Dynamic Memory: A 
Theory of Reminding and Learning in Computers 
and People. Cambridge: Cambridge Univer- 
sity Press, 1982. 

3. Schank, Roger C, and Christopher K. 
Riesbeck. Inside Computer Understanding: Five 
Programs Plus Miniatures. Hillsdale, New 
Jersey: Lawrence Erlbaum Associates, 
1981. 



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APRIL 1985 'BYTE 



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10 ea DS/DD. 40T (IBM. H/P) 

100 ea. DS/DD. 40T (IBM. H/P) 

DYSAN. 10 ea SS/DD I Apple etc) 

10 ea. DS/DD 48T(IBM,H/P) 

MAXELL 10 ea. SS/DD.MD1 (Applei 

10 ea SS/DD 3'. (MAC) 

10 ea DS'DD MD2 (IBM) 

10 ea DS/QDHiDens(IBM-AT) $ 77 

MEMOREXJOea.SS-SD 3 . [MAC 

10 ea .DS-OD Hi Dens (IBM-ATI 
VERBATIM, 10eaSS/DDMD5tW)1(Apptei 
10 ea OS/DO MD34 (IBM] 
10 ea. SS/DD 3"? (MAC) 

* GENERIK " DISKETTES * 

Top quality w/jackets no labels 
90 day "No hassle money back guarantee ' 
1 00 ea. 35 Track (Apple. Atari) 
250 ea 35 Track ( Apple Atari i 
1000 ea 35 Track (Apple Atani 
100ea 48 Track (IBM. H/P) 
250 ea 48 Track (IBM H/P) 
1000 ea 48 Track (IBM H Pi 




S 80 
199 
750 

i 95 

► 229 
.829 



MODEMS 



ANCHOR, Signalman Mark XII (IBM) 


LIST [ 
$ 399 j 


OKHOY 
t 259 


HAYES, 2400B External Modem (IBM) 


$899 J 


1699 


Smartmodem 120GB (IBM) 


$ 599 ! 


1409 


Smartcomli Software (IBM) 


$ 149 < 


1 99 


Stack Chronograph (RS-232) 


S 249 ! 


; 189 


Stack Smartmodem 300( RS-232) 


$289 ! 


1219 


Smanmodem1200(AP) 


$699 J 


5 489 


Micromodem he w/Smancom (AP) 


$329 1 


J 239 


KENSINGTON, Modem 1200 (MAC) 


$ 595 ! 


» 3es 


NOVATION, J -Cat 


$ 149 ! 


> 104 


ACCESS 1-2-3. 1200B+CrosstalkXV((IBM) $ 595 J 


i 369 


Apple Cat II 300 B (AP) 


$389 ! 


i 249 


212 Apple Cat, 1200B(AP) 


$ 725 ! 


I 559 


SmartCat Plus w/sottware (MAC) 


$499 J 


I 3/9 


PROMETHEUS ProModem 12006 (IBM) 


$399 ! 


I289 


ProModem 1200 (MAC) 


$549 ! 


I 429 


QUADRAM, Quadmodem Internal (IBM) 


$ 595 ! 


I 425 


Quadmodem External (IBM) 


$695 J 


> 49b 


VENTEL PC Half Card (IBM) 


$549 ! 


► 389 


1200 Plus, External (IBM) 


$499 ! 


I 429 


PC12O0 Internal (IBM) 


$499 J 


t 379 



MONITORS 



LIST 

AMDEK, Color 300 Comp/ Audio $ 349 

Cokx 500 Comp/VCR/ RGB/Audio $525 

Color 600 Hi Res RGB 'Audio $ 599 

Cotor 700 Ultra Hi Res RGB S 749 

Color 710 $ 799 

3O0G 12 Green $179 

3G0G 12 Amber $ 199 

31 OA IT Amoo (IBM | $230 

PRINCETON, HX-12 Hi Res RGB $ 795 

SR 12 Hi Res RGB $799 

Scan Doubter tor SR-12 $ 249 

MAX- 12 Amber (monrxhrrjrne) S 249 

QUADRAM, ArnbercfTome 12 Amber $ 250 

aiadchrome 12' RGB Color $ 695 

Quadchrome II, 14" RGB Color $ 650 

ftjadsoeen ir 968*51 2 w'cabte H. Res $1995 

ZENITH. ZVM122 12 Amber $ 159 

ZVM123, 12" Green $149 

ZVM124 12 Amber $200 

ZVM135. 12' Color S 599 



> 249 
f 395 

!459 
1549 
1599 
1 129 

H49 

i 159 
.495 
1599 
179 
1199 
1165 
J495 
i 450 
$1595 
i 95 
I 89 
I 149 
I 499, 



PRINTERS 



DOT MATRIX: 

LIST 
PRICE 

EPSON, RXM-lOOcps S 269 

RX80-F/T $ 369 

BX100— 100 cps. 136 col. pin & fr $499 

fX80-160cps.80col S699 

FX100-t60cps. 136col $849 

JX80— Color Printer. 160 cps $ 399 

LQ1500-200&67cps $1395 

Tractor Feed for LQ1 500 $ 70 

MANNESMANN TALLY. 

Spin!— 80 col 80 cps $269 

160— 80 col. 160 cps $798 

180— 132 col, 160 cps $1098 

OKIOATA, Okimate 20. Color. Hi Res $ 268 

62A— 80 col 1 20 cps. para S 349 

83A- 132 col. 120 cps. para $749 

84-136 col. 200 cps. para $899 

92— 80 col 160 cps para $499 

93— 136 col 160 cps para S 799 

241 OP-Pacemark, 350cps para $2995 

QUADRAM. Ouadje!, Inkjet Color Pnnier $ 895 

STAR MIC, Gami. 120cps 10 S 499 

Germn. 120cps 15" $ 549 

TOSHIBA, Prop spacing A Hi-res graphics 

1351-192cps(DQ)&lO0cps(LQl S1895 

1340-144cps(DG)&S4cpsaO} $995 

Bi-drectional Tractor Feed $ 195 

TTX. TTXpress portable/ handheld. 4Qcps $ 229 

LETTER QUALITY: 

JUKI. 6300-40 cps para $995 $795 

6100—18 cps para 3 pitch $ 599 $ 439 

TOSHIBA Prop spacing & Hires graphics 

1351-192 cps<DQ)& 100 cps (LQ) $1895 $1375 

l340-144cps(D0)&54cps(LQ) $995 $795 

TTX. 1014— 13 cps. para/ser p&fr 3p $ 499 $ 365 

1114— sane as 1014 w/T&F 2c & prop $ 599 $ 439 

PLOTTERS: 

AMDEK. Amptotll 6 pen 10x14 $1099 $ 899 

PRINTER SUPPLIES: 

Paper, Ribbone, Daisy Wheels 



COHHOY 
PRICE 
CALL 
CALL 
CALL 
CALL 
CALL 
CALL 
CALL 
CALL 

S 219 
$568 
S778 
!1208 
11319 
!i 599 
H729 
!399 
$649 
!H975 
!1795 
S 269 
S419 

f375 
795 
175 
129 



PRINTER INTERFACES 
& BUFFERS 



LIST 

ARBO, l BM • PC to Para Pnnter Cable $ 60 

EPSON, Parallel Interface for LQ1500 S 100 

Serial Interlace Board $ 130 

ASSJMPROC, Mac to Epson Conn l/F $ 89 

MPC, Applei I l/F & Cable for Epson & Gemini $ 95 

OKIDATA, Plug h Pay. Tractors. Otagaph.ea $ 50 

ORANGE MICRO, Grappler Plus lur Apple $ 149 

Serial Grappler $ 119 

Buffered Grappler Plus. 16K S 239 

PRACTICAL. Microbuff In-Line 64K.para $ 349 

Microciif fin- Line 64K,ser $349 
QUADRAM, Microfa/ers full line in STOCK 



S 30 

II 79 
II 105 
li 69 
1 1 59 
II 42 
li 99 
1 1 79 
!l 159 
$259 
$259 
CALL 



CABLES 



ARBO, IBM-PC to Modem Cable $ 31 I 21 

IBM-PC to Para Pnnter Cable $ 60 | 30 

ASTAR, RF Modulator tor TV (Apple) $ 35 | 20 

CURTIS, Monitor Extension Cable (IBM) S 50 I 35 

3-9 Keyboard Extens Cable (IBM | $ 40 I 30 

RCA Monitor Cable $ 15 $ 9 



ACCESSORIES 



50 



CURTIS, Diamond. 6 outlets switched 

Emerald. 6 outlets. 6' cord 

Ruby 6 outlets. 6 cord filter 

Sapphire 3 outlets, wffilter 
EPD. Lemon. 6 outlets/ wall 

Lime 6 outlets/cord 

Orange 6 outtets/corrj 

Peach 3 outlets/wait 

Kiwi. 1 outlet/wall 
INNOVATIVE, Fhp-n-File 10 (disk hotder) 

Flip-n-Fite 50 (disk hoWer) 
KENSINGTON, Masterpiece (IBM) 

System Saver Fan (Apple) 
NETWORX. Wretree 4 outlet w/lilt & surge $ 
PERFECT DATA Head Cleaning Kit $ 

PROD TECH INTL Umnterruptable Power Supply 

200 Warts PC200 tor IBM-PC $ 499 

300 Watts XT300 lor IBM- XT $ 359 

800 Watts AT800 lor IBM-AT 12 lbs 



I 

I 

S 

s 
$ 

$ 90 
$ 140 
$ 98 

$ 7 
S 22 

$ 140 
$ 90 



$ 29 

li 35 
11 52 
11 46 
11 29 
II 45 
li 60 
II 39 
CALL 

!4 
15 
99 
69 
39 
12 

S 39 

$279 

CALL 



. CONROY- 
LAPOINTE 
CREDITCARD 

Send me a ConroyLaPointe 
| credit application form so I 
, can get cash discount prices 



nRDFRINfi I MPn A TPQMQ- **"- T ° ,Z06 ° «* G «*** "*«*< ^ l «*- ®* 972Z3 M ** y«» telephone number, double 

UnUCnmU IPir \J OC I tnmO. check fan figures lw Shipping. Insurance and Handling (SIHj AH items uaoally in stock 
HO C SB Cashiers checks, money orders, fortune 1000 cheeks and government checks honored immediately Peisonal and other companv checks —allow 20 days to 
cleai Prices gfltcl 3% ash « Ctnriy-Ltftkni Cratflt Cvi tiutmt so ADD 3% to above puces for VtSA/MasterCaid-Amencan Express Your cards NOT charged til we 

ship Add SIK CHARGES: U S Mainland ,W ($5 rmnimunn for SttfKted UPS ground, UPS Blue, 6^ ($10 minimum), for US Pustat. APQ or FPO, 6% ($10 minimum) 
Alaska & Canada— Postal Fflrtlgri wders except Canada 18% ($25 mmtmums Momtms by Postal m in foreign cnuntnes 30% ($50 mktfraum) Orders received With 
insufficient StH chatges will be relunded Aft prices, avartabthty and speciftcattons subieci to errors or change without notice, so caif to venty AH goods are new include 
warranty and are guaranteed to work Due to our to* pr*ces and ooi_ assurance that_yoa wii! getnew^ unused products— *LL 3ALCS ARE FINAL. We do not guarantee 



Mmiinun-. ir ' ,t ' 111 fx,[,:,lase MAIL TO: 12060 SW Gar den P lace, Portlan d. OR 97223 



. _ reptacemem 0R8IR0ESR mm 
^tlok " IM emtrlk" in tndtnwk* el igmX Conwrilion 



compatibility Catl before returning goods lor repair 
New York. )E«m»P—" 



i wilt get new. unused products— ALL SALES ARE FINAL. We do not guarantee 
-SAM to 6PW PST MMtiiy thrMfh FrMty. Stter^y 10 it 4. (6AM here is 9 AM in 



^ w-LaPomte, me- All Rights Reserved X V^ * ^Q 




COMPUTER 
SYSTEMS 






— Call tor Details — 
256K IBM - PC 



360K 

Disk Drives 

by CDC 




SANYO »a 

256K. 2 320K Disk Drives 



TfeP* 



Z150, 

256K 2 320K Disk Dnves. 

MS DOS 2 1. 8088 Chip, 2 S/P 



HARD DISKS 



Kits are completely engineered to work with DOS 2 0/2 1 
" Includes Hard Disk. Controller Card and 



Easy to install 

Instructions 

KAMERMAN, External 1 men kit 

Meoaflight 100. Internal 10 meg kit 

Masterflight. 20 meg. tape, surge prot 
MAYNARD, Internal 10 meg kit. (WS1) 
OUAORAM. Quaddrsks Int w control ter 

FulLine 
RANA. External 10 meg w/controller 

Internal 10 meg w/controller 



LIST 
SI 295 
$895 
$3095 
SI 595 



Si 495 
$ 995 



CONWY 
5 
795 
95 
150 

CALL 

?095 
795 



FLOPPY DISK DRIVES 



COC, Limited 30 day warranty Call for quantity prices 



Full Height 
Half Height, 



$149 
$129 



MAYNARD. Controller Card w/para port S 300 f 185 

Controller Card w/senal port $310 $195 

Sandstar Corn Card (accepts 3 modules) $265 $205 

PERFECT OATA, Head Cleaning Kit $ 16 $ 12| 



StxPak Plus, 64K 

SrxPakPlus. 256K. S/PCC+S/W 

SrxPakPlus. 384K. S'WCC+S/W 

Game Port for SixPak 

Preview" Graphics Card w/para. 64K 

Advantage" Multil Bd (or AT 

1/0 Plus II. S/P/CC 

1/0 Plus II. S/P/CC/G 

l/0Plusll.2S/P/CC/G 

MonoGraphRus" P/CC (torLotus) 

PCNei. Starter Kit. PC0O2 

PCNet, Circuit Board. PC001 

ComboPlus Products IN STXK 

MegaRus Products IN STXK 
COMX. 

Econo RAM Plus". 384K to 1 5 meg 
board, S/P/CC/G. Fastrak'"& Spooler 

EconoRAM". lull 384K board 
CURTIS. UNI -I, Monitor tilt /swivel base 

3-9 foot Keyboard Extension Cable 
HA UP PAGE (HCW), 8087 Chip 

8087 Math Pak {Chip & Softw) 

8087 Software Pak 

8087 Macro Pak 
HAYES. Mach il joystick 
HERCULES Color Card w/para 

Mono Graphics Card 
KAMERMAN, External Power Supply 
KENSINGTON, Masterptece" 

PC Saver" Line Cord w/Filter 
KEY TRONIC, KB5151 Std keytjoard 

KB5150 Std keyboard 
KOALA, Speed Key System 

Speed Key Tables w/software 

Koala Pad" w PC Design 

Programmer's Gmde 
MAYNARD, SAND STAR SERIES 

Multrluiction(6iCard 

Memory Card no RAM 

Memory Card 256K 

Floppy Con) Card, accepts 3 modules 

HardOtskl/F Module 

HardDisk Cable 

Serial Port Module 

Para or Clock Cal Module ea 

Game Adapter Module 

Memory Module. OK 

Memory Module 256K 

10 meg Hard Drsk Kit & Con! Card 



$695 
$895 
S 50 

$ ; 

S! 

$215 
$ 265 
$315 

$495 
$1090 
SI 



| 395 
11465 

II 39 

$299 

S 445 

:: 150 

II 165 
S21S 
S 375 
$790 
$365 
CALL 
CALL 



$ 595 
$ 50 
$ 40 
$ 175 
$295 
$ 180 
$245 
$ 45 
$245 
$499 
$395 
$ 140 
$ 50 
$255 
$209 
$ 100 
$200 
$ 150 
$ 15 

S 89 
$ 199 

$495 
S 265 
$499 
$ 30 
$ 95 
$ 59 
S 49 
$ 122 
$422 
$1595 



$395 

$325 

II 39 
II 30 

II 149 
:: 235 
$138 
$195 
II 29 
II 169 
Il 329 
$295 

I 99 

II 35 
:; 195 

$159 

:: 63 
II 139 
II 69 
II 14 

$ 79 

$169 
II 395 
:.205 
$399 
II 27 
II 79 

:; 49 
II 43 
II 99 
li 357 
IS1150 



MICROSOFT Mouse for PC 
System Card 64K 
System Card, 256K 

MOUSE SYSTEMS PC Mouse & Pamt 

PARADISE, Modular Graphics Card 
Parallel or Serial Port, ea 

PERSYST, DEW 
PC/Mono Board, w/para port 
PC/Color Graphics Bd.w/hght pen & l/F 
"" Board" Color Adapter, In res 

PLANTRONICS. 
Color Bd & Colormagic, 16 color w/Para 
Color Bd & Draftsman. 16 color w/Para 

QUADRAM, 

Quadboard 64K. to 384K, S/P/CC/G 
Quadboard. no RAM. expand to 364K 
Ouadboard 256K, to 384 K. S/P/CC 
Quadboard, 384K. S/P/CC/G 
Quadboard II. no RAM. to 256K 
Quadboard II. 64K. to 256K. 2S/CC 
Quadboard II. 256K, 2S/CC 
Quad 512 + 64K w/senal port 
Quad 512 ♦ 256K w/senal port 
Quad 512 + 51 2K w/senal port 
Quadcoky I. board. 4 colors 
Upgrade Quadcolor I toll kit 
Ouadvue, board. Mono. S/P/CC 
Quadchrome Monitor, 12" RGB Color 
Quadcnrorne II Monitor. 14" RGB Color 
Amberchrome Monitor. IT Amber 
Quad 3278 
QuadnelVI 
QuadnetlX 
Quadtink 

TG PRODUCTS Joystick 

TITAN, Accelerator PC (8086+ 128K> 

W1CO, Smartboard Keyboard 



$ 395 $ 245 

$295 $225 

$675 11395 

$ 795 II 495 

$295 $215 

$ 395 II 265 

$ 595 1 1 395 

5 325 $ 265 

S 550 ! i 420 

$ 895 ! i 625 

$295 S195 

$275 $199 

I 345 $ 269 

$795 II 495 

$ 650 I 1 450 

$250 11165 

$1195 11050 

S2295 11545 

$1995 11745 

$495 $385 

$ 45 II 29 

$995 !1750 

$ 400 $ 279 



• * FOR YOUR PC-JR • • 



LIST 

PRICE PWCE 

KEY TRONIC, KB5151 Jr Keyboard $255 $ 195 

KOALA, Touch Tablet for Jr $125 !! 75 

MOUSE SYSTEMS, Mouse for Jr $195 11125 

MICROSOFT 128K Booster w/Mouse $495 ! 1 329 

Serial Mouse $ 195 II 139 

QUADRAM, Quadmemtr<128K-512K.P/CC> $ 275 ! i 215 

Quadjr Expansion Chassis $ 695 S 540 

TECMAR, Jr Captain $395 $ 345 



$29 



9 Each, 4164 chips 

90 Day Warranty by us 



PRICES ARE 
DROPPING, 
SO CALL' 



• ComX • 
EconoRAM Plus 



% 



% 



$395 

384K Multifunction RAM Board 
expandable to 1.5 Megabyte 

Works like AST SocPakP)us T ' r wrtti 

capacity for up to 1 5 meg. game port. 

Fastrak™ RAM Disk and Spooler Software 

EconoRAM™ 384K 

Single Function Board 



$325 



WrthFastrak" and Spotter 

FuHy Compattote, 1 Year United Warranty, 

Works on DOS 1 1.2 0or2 1 

Pnces and availability subject to change Call 



SOFTWARE FOR YOUR IBM-PC, XT, AT or JR 



BUSINESS 



APPUED SOFTWARE, VersaForm 
ASHTON-TATE, Framework 

dBase III 

dBase II, (req PC-DOS & 128K) 

dBase II to III upgrade 
ATI, Training Programs— Large Inventory 
BPI. Job Cost Accounting 

Genl Acctg. Afl. AP or PR, each 
BRODERBUND, Bank St Wnter(PC or Jr) 
CDEX, Training Programs— Large Inventory 
CONTINENTAL, Ultrafile (PC) 

Tax Advantage (PC or Jr) 

FCM (Filing. Cataloging, Mailing)(PC) 

Property Management (PC) 
DOW JONES, Investment Evaluator 

Market Manager Plus 

Market Analyzer 

Market Microscope 

Spreadsheet 
FOXAGELLER, dlltil <DOSorCPfM86) 

Quckcode or dGraph. each 
HARVARD, Total Project Manager 

Harvard Project Manager 
HAYDEN, Pe Wnter 

Pie Speller 
HOWARDSOFT, Tax Preparer lor 84 

Heal Estate Analyzer 
HUMAN EDGE, Mmd Prober (PC or Jr) 

Communications Edge (PC) 

Sates Edge 

Management Edge 

Negotiation Edge 
IUS, Easy Writer II System 

Easy Speller II 

GL AR AP. 0E or INV. each 
KENSINGTON, Easy Link Mail Manager 
UFETREE, Vohswnter Deluxe 

Volkswnter 



LIST 
PRICE 
$389 
$695 
$695 
$495 
$200 
$ 75 
$795 
$ 595 
$ 80 
$ 70 
$ 195 
$ 70 
$125 
$495 
$ 139 
$300 
$350 
$350 
$249 
$ 99 
$295 
$495 
$395 
$200 
$ 50 
$ 295 
$250 
$ 50 
S 195 
$250 
$250 
$295 
$ 350 
$ 85 
$ 595 
S 95 
$395 
$195 



CONROY 
PRICE 
$249 
!i 345 
S360 
S289 
!i 119 
II 50 
!!495 
Ji 375 
II 50 
II 45 
II 125 
!i 45 
J I 75 
!i 295 
II 99 
M59 
J1219 
II 219 
11159 
II 65 
$165 

I (SIS 

I 239 

11125 
:: 30 
::195 
:; 170 

II 32 
S119 
1 1 159 
$159 
$185 
$250 
II 125 
S375 
II 59 
!. 159 
$105 



BUSINESS 



LIST 

PRICE 

LIVING VIDEOTEX* Thmk Tank $ 195 

LOTUS, 1-2-3 $ 495 

Symphony $ 695 

MDBS, Knowledgeman $ 500 

MECA, Managing Your Money $ 195 

MICROPRO, WordStar" (PC) $ 350 

WordStar'" (Jr) $ 195 

WordStar 2000 $ 495 

WordStar 2000 Plus $ 595 

WordStar Professional Plus $ 695 

WordStar Professional. 4 Pak | 495 

MailMerge. SpeJIStar or Starlndex, ea $ 99 

Preoptions Pak ( MM /SS/SI ) $ 1 95 

InfoStar Plus (+ Startost) $ 595 

Correct Star $ 145 

MICRORIM, RBase Senes 4000 $ 495 

Extended Report Wnter $ 150 

RBase Clout $ 195 

MICROSOFT Spell $ 50 

Multiplan(PCorJr) $195 

Chart or Protect each $ 250 

Word $ 375 

Word with Mouse $ 475 

MONOGRAM, Dollars & $ense w/Forecast $ 180 

M ULTIMATE, Multimate Ver 4 $ 495 

OPEN SYS GL AR.AP.PR.INV or PO.ea $ 695 

PEACHTREE, Back to Basics GL $ 295 

PeachPak $395 

Peach Text 5000 $ 395 

QUADRAM, Tax Strategy $ 395 

investment Strategy $ 395 

QUE, Using 1-2-3 $ 15 

12-3 lor Business $ 15 

Using Symphony $ 20 

SAMNA, Word Plus $ 295 

SATELLITE, WordPerfect (PC) $ 495 

WordPerfect (Jr) $ 69 

SOFTW ARTS, TK Sotver(specif DOS) $ 399 

SOFTWARE INTL, Open Access $695 



PRICE 
$105 
S309 
S465 
S300 
II 125 

:; 189 
:;115 

S295 
I.325 
S395 
S265 
II 54 
M05 
S315 
II 77 
:269 
II 95 
M25 
II 32 

I 125 
M59 
I.235 
S 289 

II 110 
$295 
$420 
II 175 
$225 

225 
$295 
$295 
S 12 
II 12 
:: 15 
195 
235 
!i 49 
S269 
$395 



BUSINESS 



SOFTWARE PUBL, PFS Report 

PFSFile 

PFS Write 

PFS Graph 

PFS Ran 

PFS: Proof or PFS: Access, each 
SORCIM, SuperCalc III 
STONEWARE, Advanced DB Master 
THORN /EMI, Perfect Writer (PC) 

Perfect Combo (Wnter & Speller) (PC) 

Perfect Combo (Jr) (Write/ Spell/Thesaus 
VISICORP.VisiCalc4 
WARNER. Desk Organizer (PC or Jr) 



LIST 
PRICE 
$ 125 
$ 140 
$ 140 
$ 140 
$ 140 
$ 95 
$395 
$595 
$349 

$ 139 
$250 
$ 195 



PRICE 
$ 79 
II 89 
II 89 
II 89 
II 69 
II 59 
S245 
:i 395 
S179 
11199 
II 89 
! I 159 
II 125 



UTILITIES 



BORLAND, Sidekick (PC or Jr) $ 55 

Sidekick (Copabte) (PC or Jr) $ 85 

Turbo Pascal (PC or Jr) $ 55 

Toolbox (PC) $ 55 

CENTRAL POINT Copy II PC $ 40 

COMX, Fastrak'". RAM/Disk emulator & pnnter spc 

any PC/DOS or RAM Card Menu Driven $ 100 

DIGITAL RES., CP/M-86™ (PC/XT) $ 80 

C BASIC 86™ (CP/M-86) $200 

C8ASIC CocnpiterfCP/M-Se or PCD0S. ea) $ 600 

Concurrent CP/M-86™ w/wmdows $ 835 

PL/1 (PC DOS) $ 750 

Speed Prog Pkg (CP/M-86) $ 200 

DR LOGO-86 (CP/M-86) $100 

EPYX, In Stock 

FUNK SOFTWARE, Sideways $ 60 

HAYES. Smartcom II ( Data Comm | $ 1 49 

U FEBO AT Lattice C $500 

MICROSTUF, Crosstak XVI (PC or Jr) $ 195 

MICROSOFT Macro Assembler $ 100 

BASCCompler $ 395 

Busress BASIC Compiler $ 600 

CCompir $ 395 

COBOL Conptar S 700 

FORTRAN Compier $ 350 

PASCAL Compder $ 300 



S 35 

$ 55 
S 35 
$ 35 
$ 30 

jter For 
II 59 
II 39 
II 135 
S395 
$225 
S495 
II 135 
II 69 
CALL 
II 40 
II 99 
S295 
II 129 
II ~ 
$259 
$300 
!. 259 
II 459 
II 229 
II 199 



UTILITIES 



LIST CONROY 

PRICE PRICE 

MOUSE SYSTEMS, PC Paint $ 99 $ 69 

NORTON, Utilities ( 1 A pm/ns) New Version $ 1 00 $ 65 

OPEN SYSTEMS, BASIC Interpreter $195 $130 

ROSESOFT, Prokey $ 130 $ 79 

WESTERN UNION. Easy Link Mail Mngr $ 95 $ 



HOME & EDUCATIONAL 

ARMONK, Executive Suite 
BPI, Personal Accounting 
CONTINENTAL Home Accountant (Jr) 

Home Accountant Plus (PC) 
DOW JONES, Home Budget 
KOALA, Graphics Exhibitor (Jr) 
MONOGRAM, Dollars & $ense w/forecast $ 165 
SCARBOROUGH, Master Type! PC or Jr. $ 50 

Your Persona) Net Worth $ 100 

SIMON & SCHUSTER, Typing Tutor! 1 1 $ 50 



$ 40 
$ 99 
$ 75 
$ 150 
$ 139 
$ 40 



PLUS: BPI, CBS COMPREHENSIVE, DAVIDSON. 
HARCOURT PBL CORP, 



RECREATIONAL 



BLUECHIP, Millionaire. Barron Tycoon, ea S 
BRODERBUND, Large Inventory In Stock 
ELECTRONrC ARTS, Large trwiwy hi Slock 
HAYDEN, Sargon III (Chess) $ 

INFOCOM, Large Inventory In Stock 
M I C R OSOFT Flight Sinulator ( PC or Jr) $ 
ORIGIN, Ultima III (PC or Jr) $ 

PROFESSIONAL Tnvia Fever (PCor Jr) $ 
SPECTRUM HOLOBYTE, Gato $ 

SPINNAKER, President's Choice, Amazon. 

Fahrenheit Rendevouz Dragon, each $ 

SUB LOGIC, Night Mission Prtall $ 



$ 39 

CALL 
CALL 
$ 34 
CALL 
$ 33 
S 39 
I 25 
$ 25 

$ 25 

$ 27 



CASH-n-CARRY COMPUTER STORES, INC. 

Retail Sales only Call stores for local hours. 
SAN FRANCISCO — 550 Washington Street (at Mont- 
gomery, opposite the Pyramid). Interstate 80, to Highway 
480, take Washington Street Exit. CALL (415) 982-6212. 
PORTLAND, OREGON - At Park 217. Tigard at intersec- 
tion of Highways 217 and 99W. CALL (503) 620-5595. 
SEATTLE, WASH. - 3540 128th Ave. SE, Beflevue 98006. 
In (oehmann's Plaza near Factoria Square, SE of Highway 
405 & 90 and at SE 36th and Richards. CALL 641-4736. 



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Nobody does it better. Nobody can. 



ARTIFICIAL INTELLIGENCE 



THE 
LISP TUTOR 

by John R. Anderson and Brian J. Reiser 

It approaches the effectiveness 
of a human tutor 



FOR THE LAST FIVE YEARS, we have 
been studying how students learn 
mathematical logical, and program- 
ming skills. We have reached the point 
where we can develop computer- 
based tutors for such domains. This 
article discusses our work on a LISP 
tutor. LISP is one of the main pro- 
gramming languages of artificial intel- 
ligence (AI) and has gained impor- 
tance with the rising prominence of 
AI. 

Universities like ours. Carnegie- 
Mellon University (CMU), are seeing 
a rapidly increasing demand for 
courses in LISP. Many students here 
learn it as their first programming 
language. But LISP is quite difficult 
because of its symbolic nature and its 
use of recursion and because of the 
need to learn abstract AI program- 
ming techniques. We see a remark- 
able range of mastery from courses 
designed to teach LISP. Some stu- 
dents find that a single course serves 
as their entry into the world of AI; 
others leave feeling they have learned 
nothing. 

Studies of students learning such 
cognitive skills have revealed that 
private tutoring appears to be much 
more effective than conventional 



classroom instruction. Classroom 
learning involves listening to lectures, 
reading texts, and working alone on 
homework problems. Private tutoring 
provides the student with an experi- 
enced person to guide his reading 
and problem solving. In a comparison 
involving LISP, we found that students 
with private human tutors needed 
only 11 hours to learn as much as 
classroom students learned in 43 
hours. In both situations most of the 
time was spent actually trying to write 
LISP programs rather than reading or 
reviewing the instruction. The major 
role of the tutor is to make the prob- 
lem-solving episodes more effective 
learning experiences. 

Educational psychologists have ob- 
served that private tutoring is an ad- 
vantage with many different types of 
material. One study (see reference 1) 
compared students who spent the 
same amount of time learning— some 
with private tutors and some in the 
classroom— for two different subjects, 
probability and cartography. Ninety- 
eight percent of the tutored students 
did better on performance tests than 
the average classroom student did. In- 
terestingly the major benefit occurred 
with the poorer students. There was 



relatively little advantage of private 
tutoring for the best students. 

Our goal has been to develop a 
computer-based tutor that is as effec- 
tive in teaching LISP as a human tutor. 
GREATERP (Goal-Restricted Environ- 
ment for Tlitoring and Educational Re- 
search on Programming) is an attempt 
to combine artificial-intelligence tech- 
nology and a psychological theory of 
skill acquisition into an effective 
teaching device. This tutor is itself a 
large LISP program that runs under 
Franz LISP on VAXes. We have already 
begun field testing this tutor in CMU 
classrooms and have seen it lead col- 
lege students to faster, more effective 
learning of LISP programming. In this 
article, we discuss how the tutor 
works, why it is effective, and the pros- 
pects for moving a version of it to per- 
sonal computers. 

GREATERP is only one of the tutors 

{continued) 
}ohn R. Anderson is a professor of psychology 
and computer science at Carnegie-Mellon 
University. He has a Ph.D. from Stanford 
University. Brian ]. Reiser holds a Ph.D. from 
Yale University and is doing postdoctoral 
research at CMU. Write to them at Carnegie- 
Mellon University, Department of Psychology 
Schenley Park, Pittsburgh, PA 15213. 



APRIL 1985 'BYTE 159 



LISP TUTOR 



that we have developed at Carnegie- 
Mellon. The Advanced Computer 
Tlitoring Project at CMU currently has 
tutors under development for high- 
school algebra and geometry, and we 
have plans to create tutors for 
calculus and other programming lan- 
guages such as Pascal and Prolog. 
The LISP tutor provides an example 
of our approach in bringing AI tech- 
niques into educational-software 
development. 

Intelligent Tutoring 

These tutoring projects are examples 
of a particularly promising approach 
to educational software called intel- 
ligent tutoring (see reference 2). Such 
systems differ from other AI ap- 
proaches to education by their at- 
tempt to provide effective instruction 
in problem solving the way a human 
tutor does. 

There are a number of components 
typically found in an intelligent tutor- 
ing system. First, there is a domain ex- 
pert, which can actually solve the prob- 
lems. (GREATERP contains a system 
that can write LISP functions from 
problem specifications.) Second, 
there is a bug catalog, which contains 
all the possible deviations a particular 
student can make from the ideal ex- 
pert behavior. Third, there is a tutor- 
ing module, which constitutes an expert 
system for instruction. It is based on 
three sets of principles: one for deter- 
mining from a student's behavior 
what he knows and what confusions 
or bugs he has, another for deciding 
when to interrupt him in the problem- 
solving process and what to say and 
a third to figure out what problems a 
student should do and when he 
should advance to new material. 
Typically, these decisions are based 
on an internal model that the tutor 
keeps of the student's knowledge and 
difficulties so far, enabling it to tailor 
its instruction to each individual 
student. 

Finally, the tutoring system must 
contain an interface for communicat- 
ing with the student. Its construction 
requires human-engineering decisions 
concerning how to present informa- 
tion understandably, how to query the 



student, how the student should enter 
answers, and what information should 
be maintained on the screen. 

Until recently, intelligent tutoring 
was a topic for advanced research but 
didn't seem to offer a viable method 
for delivering educational software 
This situation has changed for two 
reasons. First, an increasing expertise 
in cognitive psychology and artificial 
intelligence allows us to build such 
tutors much more efficiently and 
rapidly. For example, we can develop 
lesson material on our LISP tutor at 
a faster rate than that estimated for 
conventional educational software 
(200 hours per hour of instruction). 
Second, while an intelligent tutor re- 
quires a larger, faster computer, hard- 
ware costs are dropping to where it 
is becoming cost-effective to purchase 
the equipment required. 

Design of the LISP Tutor 

The goal underlying our design of the 
LISP tutor is simple: A student should 
be able to work on a problem in a 
"friendly" environment, as if he were 
using a smart, structured editor. How- 
ever, whenever he makes a planning 
or coding error or asks for help, the 
tutor should provide helpful informa- 
tion that guides the student back to 
a correct path to the solution. In ad- 
dition, we wanted our tutoring en- 
vironment to represent the concep- 
tual structure of programming prob- 
lems better than a simple screen 
editor. 

In order to monitor a student's 
progress and discover and instruct 
about errors, the tutor must be able 
to solve the problems the student is 
working on. Therefore, the first com- 
ponent in the LISP tutor is the ideal 
model, a simulation of the program- 
ming knowledge ideal students use in 
solving problems. This ideal model is 
based on a detailed theory of how 
students learn to program (see refer- 
ence 3). 

We used GRAPES (Goal-Restricted 
Production System, see reference 4) 
to represent the rules programmers 
have for solving problems. Each prob- 
lem-solving rule is represented in the 
system as a production rule. Each pro- 



duction rule contains an IF part, which 
is a set of conditions used to deter- 
mine if the rule applies, and a THEN 
part, which specifies what to do in 
that situation. The following are 
English versions of two of the hun- 
dreds of GRAPES production rules 
known by the tutor: 

IF the goal is to combine LIST1 
and LIST2 into a single list 

THEN use the function APPEND and 
set as subgoals to code LIST1 
and LIST2 

IF the goal is to check that a 
recursive call to a function will 
terminate and the recursive 
call is in the context of a MAP 
function 

THEN set as a subgoal to establish 
that the list provided to the 
MAP function will always 
become NIL after some 
number of recursive calls 

The first is a straightforward produc- 
tion rule about the use of the LISP 
function APPEND to make one list 
from two other lists. The second is a 
rather esoteric production rule that an 
advanced programmer might have. 
When the ideal model codes a LISP 
function, it applies many production 
rules like these to plan and then write 
the code. It also contains a large set 
of buggy rules that represent mis- 
conceptions novice programmers 
often develop during learning. 

The ideal model represents the 
knowledge we want the student to ac- 
quire. But the tutor must also repre- 
sent what he currently knows or does 
not know and his approach to each 
particular problem. The tutor follows 
the student as he types in his code, 
symbol by symbol, and tries to figure 
out what correct or buggy production 
rule would have led to that input. If 
the rule found is a correct one, then 
the tutor stays silent and waits for fur- 
ther input. If, on the other hand, the 
input is in error, the tutor interrupts 
with advice. Thus, as long as the stu- 
dent follows a path leading to a cor- 
rect solution, the tutor stays in the 
background. 

{continued) 



160 B YTE • APRIL 1985 



Put your blue box 
out to pasture. 



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You get performance as well as flexibility 
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ASM 86 assembler running under ACCESS on 
an IBM PC AT runs 4.7 times as fast as the 
assembler on a hard-disk based Series III 
and an incredible eleven times faster than a 




floppy-disk based Intel system. The ASM 86 
assembler we tested under ACCESS even 
ran 1.53 times faster than a VAX 11/782 
running competing cross-software. 

Genesis Is Easier to Use. 

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Telex: 4998093 GENMSUI 

Inquiry 165 




f 









. ^I^^^^^H 






— — 


—-as 






■ 


■.•>.* * *Z# ■* 



LISP TUTOR 



The LISP tutor works 
through the algorithm 
step by step. 



The LISP tutor is designed to pro- 
vide as much guidance as necessary. 
When it finds that the student is hav- 
ing difficulty coding a problem, it 
takes him from "coding mode" into 
"planning mode"; that is, the tutor 
works through the algorithm with the 
student, step by step, using an exam- 
ple. After the algorithm is con- 
structed, the student can return to 
coding, presumably with a better idea 
of what he should do to get his code 
to work properly. 

We have designed this tutor with a 
strong commitment to immediate 
feedback. As soon as the student 
makes a mistake, the tutor responds 
with an appropriate diagnostic mes- 
sage. Because a student can write his 
code a small piece at a time, the feed- 
back appears as soon as one item is 
wrong. By contrast, in the standard 
learning situation a student only 
receives feedback after he codes the 
entire function— or set of functions— 
and tries to run it. There is con- 
siderable psychological evidence that 
humans learn better with immediate 
feedback. 

The tutor also provides guidance by 
hinting toward the correct solution if 
the student is having difficulty. These 
hints take the form of queries and re- 
minders about current goals. If nec- 
essary, the tutor can provide the next 
small piece of code so that the stu- 
dent can continue. This is done at the 
student's request or after he has 
made more than the maximum 
number of allowed errors— usually 
two— for that portion of code. The 
goal here is for the student to do as 
much of the work as possible. Stu- 
dents learn much more effectively by 
doing than by watching. By providing 
the next portion of code, the tutor 
enables the student to work through 
the rest of the problem in cases where 
he might otherwise have given up. As 



a consequence, he can tackle more 
and more difficult problems. 

A major design feature of the tutor- 
ing interface provides the student 
with a structured editor through which 
to enter code. This editor automatical- 
ly balances parentheses and provides 
placeholders for the arguments of 
each function. For example, to write 
a function definition in LISP, you must 
use the function defun followed by 
the function name, a parameter list, 
and the function body. To begin, the 
student types a left parenthesis and 
the word defun. As soon as he types 
the space following that word, the 
tutor redisplays the code as 

(defun <NAME> < PARAMETERS > 
< PROCESS > 
) 

The symbols in angle brackets in- 
dicate arguments that must be coded. 
The tutor places the cursor under- 
neath < NAME> and highlights it to 
indicate that the function name must 
be coded next. 

This structured editor relieves stu- 
dents of the burden of balancing paren- 
theses and checking syntax. It enables 
them to focus on the more conceptual- 
ly difficult aspects of LISP. Our results 
show that this leads to faster learning 
of these major techniques and skills — 
with no deficit in syntax knowledge. 
Students removed from the tutor per- 
form as well as or better on all aspects 
of coding, including algorithm design, 
memory for LISP functions, and syn- 
tax, than those conventionally taught. 

The editor also facilitates commu- 
nication between the student and the 
tutor. Our studies of interfaces have 
shown that in the normal question- 
and-answer format of most educa- 
tional software, the tutor and the stu- 
dent can easily get "out of sync" on 
complex problems, where the student 
is not sure what part of the problem 
the tutor is talking about. In the LISP 
tutor, the student types directly into 
the code, replacing one of the place- 
holders, and thus it is always clear 
what part of the problem is being 
coded. Furthermore, these symbols 
help to communicate the conceptual 
structure of the programming prob- 



lem. For example, when the student 
types the iterative construct prog, the 
tutor provides the template for 
iteration: 

(prog < LOCAL VARIABLES > 
<INITIALIZATIONS> 
<BODY> 
<REPEAT> 
) 

This template helps to structure the 
problem into a list of local variables, 
initializations of those variables, code 
for the program body (i.e., the re- 
peated actions), and a return to the 
start of the loop. In many cases a sym- 
bol is expanded into more detailed 
symbols; for example, the < BODY> 
is coded as two portions: a 
TERMINATING CASE> and the 
< UPDATING CODE>. 

When an error arises or the student 
requests assistance, the tutor con- 
structs an English explanation based 
on templates associated with each 
production rule. These explanation 
templates allow the tutor to describe 
an error or provide a hint by using a 
general rule and making reference to 
the specific problem being coded. 
However, writing programs to under- 
stand natural language is an enormous- 
ly difficult and expensive task. In fact, 
students' descriptions of their algo- 
rithms are often hard for even human 
tutors to understand. Therefore, when 
the student is working with the tutor 
to design an algorithm, rather than 
having him type in English responses 
to the tutor's questions, we provide a 
menu of choices for his responses. 
This menu is constructed from the 
English descriptions of the correct 
and buggy production rules under 
consideration. 

Learning LISP 
with the Tutor 

Currently the LISP tutor contains ap- 
proximately 32 5 production rules 
about planning and writing LISP pro- 
grams and 475 buggy versions of 
those rules. It is effective in diagnos- 
ing and responding to between 45 
and 80 percent of the student's errors, 
depending on the complexity of the 

{continued) 



162 BYTE • APRIL 1985 



Move over, Crosstalk 




The NightOwrs in town 
and he's packing a 
16-bit MEX! 



Last year, the NightOwl 
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NightOwl 



Inquiry 284 



APRIL 1985 -BYTE 163 



LISP TUTOR 



T^ble 1: The LISP curriculum. 

1. Basic LISP functions 

2. Defining new function 

3. Conditionals and predicates 

4. Structured programming 

5. Progs, input/output, and evaluation 

6. Integer-based iteration 

7. Integer- based recursion 

8. List- based recursion 

9. Li st- based iteration 

10. Advanced recursion 

11. Advanced programming constructs: Maps, Dos, Lets 

12. Property lists and arrays 

13. Search techniques 

14. An advanced problem: Waterjug 

15. List structure and destructive functions 

16. Macros and advanced function types 
17 Advanced topic: Pattern Matching 

18. Advanced topic: Implementing Production Systems 



Listing 1: The dialogue between student and computer tutor to define the 
function rightp. 

Define rightp. It takes 3 arguments, sidel, side2, and side3, which represent the 
lengths of the three sides of a given triangle, where side3 is the longest side, rightp 
tests whether the three sides form a right triangle. In a right triangle, the sum of the 
squares of sidel and side2 is equal to the square of side3. However, your function 
should allow for a measurement error of 2 percent. In other words, your function 
should return t if the sum of the squares of the first two sides is within 2 percent of 
the square of the third side, 

For example (rightp 3 4 5.01) = t, because 3 squared + 4 squared = 25, which is 
within 2 percent of 5,01 squared. 

1. (defun rightp (sidel side2 side3) (cond)) 

Yes, you could use cond here, but there is a much easier way to test if the sum 
of the squares of the first two sides is within 2 percent of the square of the third. 
You can use a predicate, since we only have one test to do. 

2. (defun rightp (sidel side2 side3) 

(lessp (difference) <NUM2>)) 

You want to code the amount of difference between the sum of the squares of 
the first two sides and the square of the third side, and you do not care which 
of those two numbers is larger. So we want to take the absolute value of their 
difference. 

3. (defun rightp (sidel side2 side3) 

(lessp (abs (difference <NUM3> <NUM4>)) 
<NUM2>)) 

Which do you want to do first? 
PRESS: IF YOU WANT TO: 

1 Write code to get the sum of the squares of the first two sides. 

2 Write code to get the square of the third side. 

Menu choice: 1 



4. (defun rightp (sidel side2 side3) 

(lessp (abs (difference (plus) <NUM4>)) 
<NUM2>)) 



[continued) 



Each lesson takes 
from one to four 
hours to complete. 



lesson and the amount of testing we 
have conducted. The curriculum we 
have designed is shown in table 1. The 
system successfully tutors students 
through problems on lessons 1 to 10, 
each lesson taking from one to four 
hours to complete. Each topic in- 
volves a small instructional booklet 
and many problems practicing the 
skills taught in that lesson. Our goal 
in designing these booklets was to 
keep the written instruction to a mini- 
mum. There is considerable evidence 
that written technical instruction is 
most effective when it is brief (see 
reference 5). 

Most of the time in any lesson is 
spent going through problems. List- 
ings 1 and 2 illustrate sample dia- 
logues in which the tutor monitors the 
student's progress through simple 
problems. This does not present the 
tutor as it really appears. Instead, it 
shows essentially teletypewriter versions 
of the student-tutor dialogue. The ac- 
tual interaction involves the use of 
several display windows: a code window 
in which the student types the code, 
a tutoring window in which tutoring feed- 
back is displayed, and a goals window 
in which reminders are presented. 

In the teletypewriter versions the 
tutor's output is given in normal type 
characters, while the student's input 
is shown in bold characters. These list- 
ings present "snapshots" of the inter- 
action; each time the student pro- 
vokes a response, we have listed his 
input along with the tutor's response 
(numbered for convenience). The total 
code as it appears on the screen is 
shown, although the student has 
added only what is different from the 
previous code {shown in boldface 
type). For example, in line 2 of listing 
1 he has typed (lessp (difference as 
an extension of the code in line 1. 

It is important to note several things 

{continued) 



164 B YTE • APRIL 1985 



MICRO CAP and MICRO LOGIC 
put your engineers on line.. 

not in line 














/vfxr/ 




/Vl^OWM IVOl?KSr/tT»^H 




c 



'I I7*«e#'<.-' 



P 



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"Typical MICROCAP Transient Analysis 



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'Typical MICROLOGIC Diagram " 



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Inquiry 361 



Inquiry 149 



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COMPUTERS & TERMINALS 



ADDS QUME 

ALTOS SANYO 

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LISP TUTOR 



No. You should create a helping function for this code, rather than coding it 
directly. Our function, rightp, is now 4 levels of embedding deep, and the rela- 
tion we are about to code— the sum of squares of two numbers— would be a 
useful helping function. Thus, let's code the sum of the squares of the first two 
sides using a helping function. 

5. (defun rightp (sidel side2 side3) 

(lessp (abs (difference (sumsq <ARGUMENTS>) <NUM4>)) 
<NUM2>)) 

What do you want the helping function sumsq to do? 
PRESS: IF YOU WANT TO: 

1 Take 2 arguments, the square of the first side and the square of the 
second side. Compute their sum. 

2 Take 2 arguments, the first side and the second side. Compute the 
sum of the squares of these numbers. 

3 Have the tutor choose. 

Menu choice: 1 

No. We wouldn't need a helping function just to compute the sum of two 
numbers. You should create your helping function so that it does more than just 
a sum. 

It would be better to define sumsq so that it takes two arguments, in this case. 
[1] the first side, and [2] the second side, and computes the sum of the squares 
of these numbers. 

Menu choice: 2 

6. (defun rightp (sidel side2 side3) 

(lessp (abs (difference (sumsq sidel side2) (times))) 
<NUM2>)) 

You should use a helping function that you have already coded, square. Since 
this function computes the square of a number, you can use it to code the 
square of the third side. 

7. (defun rightp (sidel side2 side3) 

(lessp (abs (difference (sumsq sidel side2) (square side3))) (plus))) 

I don't understand that, Rob. How are you going to code 2 percent of the 
square of the third side? 

[EXPLAIN] 

OK. I'll explain what I wanted. You qould either code this directly or create a 
helping function here to code 2 percent of the square of the third side. Let's 
create a helping function just to make things easier. We'll call this helping func- 
tion percentage. We will define percentage when we are finished coding rightp. 

What do you want the helping function percentage to do? 
PRESS: IF YOU WANT TO: 

1 Take 2 arguments, one hundredth of 2 and the square of the third 
side, Compute their product. 

2 Take 2 arguments, 2 and the third side. Compute the given percent- 
age of the square of its second argument. 

3 Take 2 arguments, 2 and the square of the third side. Compute the 
given percentage of its second argument 

4 Take 1 argument, the square of the third side. Compute 2 percent of 
its argument. 

5 Have the tutor choose. 

Menu choice: 3 
Very good. 

8. (defun rightp (sidel side2 side3) 

(lessp (abs (difference (sumsq sidel side2) (square side3))) 
(percentage 2 (square side3)))) 

{continued) 



166 B YTE • APRIL 1985 




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LISP TUTOR 



about these dialogues. First, recall 
that the tutor balances parentheses 
and provides placeholders (e.g., 
<CASE>, <NAME>, <NUM>) 
for portions of code that need ex- 



panding. Second, despite the large 
portions of code added from one line 
to the next, it understands each 
separate word or symbol the student 
enters, and it responds with an error 



OK. Now we have finished coding the function rightp. Let us now code the 
helping function(s) we used but haven't yet defined. 

Which do you want to do first? 
PRESS: IF YOU WANT TO: 

1 Define the helping function sumsq. 

2 Define the helping function percentage. 

Menu choice: 1 

Define the helping function sumsq. It takes 2 arguments. (num1 num2) are the 
suggested names for the arguments, but you may name them whatever you 
wish, sumsq should compute the sum of the squares of numl and num2. 

9. (defun sumsq (s y) 

(plus (square s) (square y))) 

OK. Now we have finished coding the function sumsq. Let us now code the 
helping function(s) we used but haven't yet defined. 

Define the helping function percentage. It takes 2 arguments, (pent total) are the 
suggested names for these arguments, but you may name them whatever you 
wish, percentage should compute pent percent of total. 

10. (defun percentage (x y) 

< PROCESS > 

[EXPLAIN] 

OK. I'll explain what I wanted. Let's figure out how to code x percent of the 
second number. 

How can you code x percent of the second number? 
PRESS: IF YOU WANT TO: 

1 Multiply the second number by one-hundredth of x. 

2 Multiply the second number by x. 

3 Divide the second number by 100. 

4 Have the tutor choose. 

Menu choice: 1 
Good. 

11. (defun percentage (x y) 

(times <NUM1> <NUM2>)) 

What do you want to do first? 
PRESS: IF YOU WANT TO: 

1 Write code to get one-hundredth of the first number, 

2 Write code to get the second number. 

Menu choice: 1 

12. (defun percentage (x y) 

(times (quotient x .01) <NUM2>)) 

No, that is not the right number. How are you going to specify one hundred in 
LISP? 

13. (defun percentage (x y) 

(times (quotient x 100) y)) 

OK. Now we have finished coding the function percentage. There are no more 
helping functions to define. 



message if necessary for any of those 
items. 

THE rightp PROBLEM 

Listing l presents a dialogue from 
lesson 4 that focuses on decompos- 
ing a problem into a set of subfunc- 
tions. Although this dialogue contains 
more errors than the typical student 
makes, it is a good illustration of how 
the tutor responds to errors and re- 
quests for assistance. The student is 
allowed to input information until he 
types cond, at which point the tutor 
tells him that a conditional structure 
is not necessary. (The actual screen 
setup is shown in figure L) Next he 
types (lessp (difference (line 2) and 
receives a hint; he correctly inserts the 
absolute value function (abs) before 
difference in line 3. Note that the tutor 
presents a menu when it doesn't 
know what the student will do next. 
For instance, since the arguments to 
difference in rightp can be in either 
order, it needs to know which one will 
be typed next, and it asks him via the 
menu following line 3. 

After line 4 the tutor gives the stu- 
dent information about when it is use- 
ful to code a separate helping func- 
tion. It queries him after line 5 to 
make sure they agree on what that 
helping function will compute. This is 
an example of the tutor's planning 
mode. In this case, the student is 
mistaken about what the subf unction 
should do; the tutor corrects him. 
After line 7 it determines that his code 
will not achieve the goal. However, 
this input does not match any of the 
buggy rules in the ideal model, so the 
tutor provides minimal feedback: it in- 
dicates that it cannot understand the 
input and queries the student to re- 
mind him about what he should be 
trying to code. This hint is not enough 
for the student, who asks for an ex- 
planation by hitting a special key 
whereupon the tutor helps him 
specify another helping function, 
percentage. 

The final form of rightp is displayed 
in line 8. In line 9 the student defines 
the helping function sumsq without 
error and goes on to define percent- 

{continued} 



168 B YTE • APRIL 1985 



Inside Outside 






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money order, or order by credit card. Per- 
sonal checks, allow 18 days to clear. 
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Sat. 9:00 a.m.-l:00 p.m. PST 

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Inside California 

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London (01) 223-4569 
Paris (01) 321-5316 
Sydney (02) 579-3322 

©Qubie' 1984 






LISP TUTOR 



age in line 10. He is stuck as to what 
to do after typing the function body 
and requests an explanation. The 
tutor helps him refine his algorithm. 
After this he defines percentage with 
one error in line 12. 



After the student defines rightp and 
its helping functions, the. LISP tutor 
puts him into a real LISP environment 
where he can experiment with them 
and try variations. After he experi- 
ments to his satisfaction, the tutor 



Yes, you could use COND here, but there is a much easier 
way to test if the sum of the squares of the first two sides 
is within 2% of the square of the third You can use a 
predicate, since we only have one test to do. 



CODE FOR rightp 



(defun rightp (sidel side2 side3) 
(cond ) 



GOALS 



Define the function rightp (rightp 3 4 5.01) = t. 
*** Test if the triangle is a right triangle. 



Figure 1: The screen configuration after line 1 in listing 1. 



In examples A and B what do you have to do to get the result 

of fact called with n? 

PRESS: IF YOU WANT TO: 

1 . Multiply n by one less than n. 

2. Multiply n by fact of one less than n, 

3 Add n to the result of fact called with one less than n. 

4. Have the tutor choose. 

Menu Choice: 2 



CODE FOR fact 



(defun fact (n) 

(cond ((zerop n) 1) 

< RECURSIVE-CASE >)) 



EXAMPLES 



fact (n) 
(fact 1) = 
(fact 3) = 



fact (n-1) 
(fact 0) = 1 
(fact 2) = 2 



Figure 2: The screen configuration before line 4 in listing 2. 



provides the next problem in the 
lesson. 

The fact Problem 

Listing 2 illustrates how the tutor 
guides the coding of a recursive func- 
tion such as finding the factorial of a 
number, an early problem in lesson 
7. Although the student has some dif- 
ficulty with the syntax of the condi- 
tional test in lines 1 and 2, he basically 
codes the terminating test correctly 
Typically, we find students have little 
difficulty with terminating cases but 
great difficulty with recursive cases. 
The dialogue after line 3 shows how 
the tutor guides the student through 
the design of the recursive function. 
It leads him to construct examples of 
the relationship between fact (n) and 
fact (n-1) and then asks him to iden- 
tify the general relationship. Figure 2 
shows the screen image at a critical 
point in the design of this function. 

The dialogue after this point shows 
two classic errors students make in 
defining recursive functions. The first 
in line 4 is to call the function direct- 
ly without combining the recursive 
call with other elements. The second, 
in line 6, is to call the function recur- 
sively with the same argument rather 
than a simpler one. 

After the student finishes coding the 
function, he goes to the LISP window 
and experiments with it. He must 
trace the function and the recursive 
calls embed and unravel. Figure 3 
shows the screen image at this point, 
with the code on top and the trace 
below it. 

Evaluating the LISP Tutor 

We should emphasize that the tutorial 
knowledge in these interactions was 
not especially handcrafted for these 
problems; it shows the general ap- 
proach used by the tutor. That is the 
power of an intelligent tutoring 
system. Once we have a system that 
can tutor recursion problems, for ex- 
ample, we can easily add problems on 
that topic. Furthermore, although 
some testing is necessary to build our 
catalog of student errors and miscon- 
ceptions, once coded, the tutor can 

{continued) 



170 BYTE • APRIL 1985 



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FOLLOWING DISKETTE FORMATS: 

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APRIL 1985 -BYTE 171 



LISP TUTOR 



- YOU ARE DONE TYPE NEXT TO GO ON AFTER 

- TESTING THE FUNCTIONS YOU HAVE DEFINED - 

(defun fact (n) 

(cond {(zerop n) 1) 

(t (times n (fact (sub! n)))))) 



THE LISP WINDOW 



= > (trace (act) 
(fact) 

• > (fact 3) 

1 < Enter > fact (3) 

2 < Enter > fact (2) 
3 < Enter > fact (1) 
|4 < Enter > fact (0) 
|4 <EXIT> fact 1 
3 <EXIT> fact 1 

2 <EXIT> fact 2 
1 <EXIT> fact 6 
6 



Figure 3: The screen configuration at the end of the dialogue in listing 2. 



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lead students through a variety of cor- 
rect solutions and respond to a wide 
range of errors. Thus, it is generative 
in the sense that it creates instruc- 
tional interactions rather than using 
preprogrammed sequences. 

Generally, students are happy with 
the tutor and rate it better than learn- 
ing experiences they have had in 
other introductory programming 
courses. Their major complaints are 
that it uses too many menus and is 
sometimes slow. We are implement- 
ing optimizations and improvements 
to resolve both these problems. Inter- 
estingly students are more appre- 
ciative of the tutors guidance and 
more tolerant of its speed as the 
lessons increase in difficulty 

We have run one evaluation of the 
tutor, comparing it to experienced 
private human tutors and 4, on-your- 
own" condition. We found that the ad- 
vantage of private tutoring— human or 
computer— over the on-your-own con- 
dition increased as the material 
became more difficult. The students 
finished lesson 1 basically with the 
same speed and success in all three 
conditions. However, those in the on- 
your-own condition often had great 
difficulty getting through the recur- 
sion material; in fact, some did not 
finish the material in the allotted time. 
We had to extrapolate how long it 
would have taken them to finish it. 
Averaging the actual and extrapolated 
times, the students took 11.4 hours 
with the human tutors, 1 5 hours with 
the computer tutor, and 26.5 hours 
"on-your-own" to learn six lessons. 
Polls of students in a traditional 
classroom suggest that it takes over 
40 hours to cover the material in that 
situation. 

We tested the three groups just 
before the recursion exercises. We 
found essentially identical perfor- 
mances even though they were learn- 
ing at different rates. In another 
evaluation, we found students work- 
ing with the tutor learned nine lessons 
of material faster and performed bet- 
ter on competence tests than students 
learning without the tutor. Thus, the 
basic conclusion is that the human 

(continued) 



172 BYTE • APRIL 1985 




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APRIL 1985 • BYTE 173 



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LISP TUTOR 



Listing 2: The dialogue involved in defining the function fact, which computes 
the factorial of the number given. 



Define the function fact. It takes a number argument, n, and computes the factorial 
of n, which is the result of multiplying n x n-1 x n-2 ... x 1. For instance, 
(fact 3) = 3 x 2 x 1 = 6. By definition, the factorial of is 1. 

1. {defun fact (n) 

(cond ((equal) < ACTION >) 
<RECURSIVECASE>)) 

I assume that you are trying to test if the number argument is equal to the 
number zero. There is a special function for testing equivalence to zero. Try to 
use that function instead of equal. 

What code can you write to test if the condition for terminating case is true? Try 
writing a predicate. 

2. (defun fact (n) 

(cond ((zero < ACTION >) 
<RECURSIVECASE>)) 

Did you mean zerop (y or n)? y 



(defun fact (n) 
(cond ((zerop n) 1) 

<RECURSIVECASE>)) 


Is the value of fact in the recursive cases calculated by; 
PRESS: IF YOU WANT TO: 


1 Calling fact recursively with n. 

2 Multiplying n by fact of n minus 1, 

3 Getting 1 2 ... n and then multiplying the results. 

4 Have the tutor choose. 


Menu choice: 3 



That is a reasonable way to think of doing factorials but it is not a plan for a 
recursive function. Since you seem to be having trouble with the recursive cases 
let us work through some examples and figure out the conditions and actions 
for each of these cases. 

The recursive relationship is the relationship between fact called with n and fact 

called with: 

PRESS: IF YOU WANT TO: 

1 n minus 1 

2 n equal to 

3 n plus 1 

4 Have the tutor choose. 

Menu choice; 1 

We will consider some concrete examples. We will characterize the recursive 
relationship between fact called with 1 and fact called with 0. 

What is the value of (fact 1)? 
Answer: 1 

What is the value of (fact 0)? 
Answer: 1 

EXAMPLES 
fact (n) fact (n-1) 

A. (fact 1) = 1 (fact 0) - 1 

We will consider some more concrete examples. We will characterize the recur- 
sive relationship between fact called with 3 and fact called with 2. 

What is the value of (fact 3)? 
Answer: 6 

{continued) 



174 B YTE • APRIL 1985 



LISP TUTOR 



What is the value of (fact 2)? 
Answer: 2 

EXAMPLES 
fact (n) fact (n - 1) 

A. (fact 1) - 1 (fact 0) = 1 

B. (fact 3) = 6 (fact 2) = 2 

Since there is only one recursive case characterized by the examples you have 
just worked out, the condition in this case can be just coded as T. We will focus 
on characterizing the action in this case. 

In examples A and B what do you have to do to get the result of fact called 

with n? 

PRESS: IF YOU WANT TO: 

1 Multiply n by one less than n, 

2 Multiply n by fact of one less than n. 

3 Add n to the result of fact called with one less than n. 

4 Have the tutor choose 

Menu choice: 2 

We have now worked through a series of examples that illustrate the recursive 
relation. We will now return to the goal of trying to produce LISP code that 
specifies the recursive relation. 

(defun fact (n) 
(cond ((zerop n) 1) 
(t (fact ))) 

You will have to use fact at some point but right now you want to multiply. 

(defun fact (n) 
(cond ((zerop n) 1) 
(t (times <NUM> <NUM2>)))) 

What do you want to do first? 
PRESS: IF YOU WANT TO: 

1 Write code to get the number argument. 

2 Write code to get the recursive part. 

Menu choice: 1 

(defun fact (n) 
(cond ((zerop n) 1) 
(t (times n (fact n))))) 

You cannot just code n at this point. What you want to do is subtract one from 
n. 

(defun fad (n) 
(cond ((zerop n) 1) 
(t (times n (fact (difference )))))) 

difference would work in this case but it is more appropriate to use the function 
subl when you are subtracting 1 from a number. 

(defun fact (n) 
(cond ((zerop n) 1) 
(t (times n (fact (subl n)))))) 



tutor is still best, the computer tutor 
not that far behind (and constantly im- 
proving), and the traditional on-your- 
own condition much worse. 

Today and Tomorrow 

Currently, we get satisfactory perfor- 
mance of the tutor on a VAX 72 5 with 



3 megabytes of memory devoted to 
a single student. Our planned op- 
timizations should enable it to handle 
a pair of students simultaneously run- 
ning on the same machine. These im- 
plementations are cost-effective in ex- 
pensive private schools like CMU or 
in industry; however, they are clearly 



out of range for the general public. 
The amount of computational power 
required is considerable. Even in 
future more efficient implementa- 
tions we estimate a minimum of 1 
megabyte of memory will be neces- 
sary to tutor one student on one 
machine. By the late 1980s the com- 
putational power to deliver such in- 
struction should be more generally 
available. For instance, in conjunction 
with IBM, CMU is planning to have on 
campus by 1986 a personal computer 
with 1 megabyte of memory capable 
of 1 million instructions per second. 
Such a machine will be more than 
adequate to implement the LISP tutor. 
These technological trends en- 
courage optimism about the future of 
intelligent tutoring efforts, of which 
the LISP tutor is one. We hope that, 
with continued research in domains 
such as high-school mathematics and 
college-level programming, we will 
soon establish the conceptual foun- 
dations to use the computational 
power that will be available. The pros- 
pect is great of providing every stu- 
dent with the educational benefits of 
a private human tutor. When this hap- 
pens, the consequences for American 
education will be nothing short of 
revolutionary ■ 

ACKNOWLEDGMENT 
This research is supported by Office of 
Naval Research under Contract No. 
N00014-84-0064. We would like to 
acknowledge the considerable contribu- 
tions of Robert Farrell. Elliot Jaffe. Beth 
Marvel, and Peter Pirolli to the research 
on the LISP tutor. 

REFERENCES 

1. Bloom, B S. "The 2 Sigma Problem: The 
Search for Methods of Group Instruction 
as Effective as One-to-One Tutoring." 
Educational Researcher, 13, 1984, page 3. 

2. Sleeman, D., and I. S. Brown, eds. Intel- 
ligent storing Systems. New York: Academic 
Press. 1982. 

3. Anderson, I. R., R. Farrell, and R. Sauers. 
"Learning to Program in LISP" Cognitive 
Science. 8, 1984, page 87. 

4. Sauers, R., and R. Farrell. CRAPES User's 
Manual Technical Report ONR-82-3. Pitts- 
burgh: Carnegie-Mellon University, 1982. 

5. Carroll, I. M. "Minimalist Training." 
Datamation, November 1984, page 125. 



APRIL 1985 -BYTE 175 



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ARTIFICIAL INTELLIGENCE 



PROUST 



by W. Lewis Johnson and Elliot Soloway 



PROUST (Program Understander for 
Students) is a knowledge-based sys- 
tem that finds nonsyntactic bugs in 
Pascal programs written by novice 
programmers. When students com- 
pile a program successfully, PROUST 
is automatically invoked to analyze it. 
PROUST reports any bugs that are in 
the program to the student. 

PROUST is not merely a tool that 
helps programmers find bugs, nor is 
it confined to a narrow class of bugs, 
such as uninitialized variables. It is 
designed to find every bug in most 
beginners' programs. PROUST is cur- 
rently capable of correctly identifying 
all of the bugs in over 70 percent of 
the programs that students write 
when we assign them moderately 
complex programming problems. 
When PROUST finds a bug, it does 
not simply point to the lines of code 
that are wrong; instead, it determines 
how the bug can be corrected and 
suggests why the bug arose in the first 
place. Our aim is to build an instruc- 
tional system around PROUST that 
assigns programming problems to 
students, reads their work, and gives 
them helpful suggestions. 

In designing PROUST we found it 
necessary to deal directly with the 



An automatic debugger 
for Pascal programs 

variability of bugs in beginners' pro- 
grams. If a programming problem is 
assigned to a class of 200, the 
students will write 200 different pro- 
grams (assuming that they do not 
cheat). There is variability both in their 
programs' designs and bugs. Some 
bugs, such as missing variable ini- 
tializations, are accidental omissions 
that can be easily recognized and cor- 
rected. Other bugs result when the 
programmer fails to reason through 
the interactions between com- 
ponents. In isolation, each piece of 
the program may appear correct, but 
when combined, the program doesn't 
work. Still other bugs result from 
misconceptions about programming. 
The code may appear correct to the 
programmer, but it doesn't do what 
he or she expects, for reasons he or 
she does not understand. Bugs result- 
ing from misconceptions are the most 
serious; students stand to benefit the 
most from having such problems 
pointed out to them. 

If a debugging system is to cope 
with the various types of errors that 
programmers make, it must under- 
stand what the programmer is trying 
to do. Debugging systems usually 
don't concern themselves with what 



the program is supposed to do, they 
only analyze what the program actual- 
ly does (see references 1,2, and 3). 
Figuring out how a program is sup- 
posed to work is not easy; to do it a 
debugger requires information about 
the programming problem and knowl- 
edge about how to write programs. 
Nevertheless, identifying the program- 
mer's intentions is worth the effort, 
because this knowledge makes it 
possible to identify more bugs, as well 
"as to understand their causes. 
Tb show how knowledge of the pro- 

{continued) 
W Lewis lohnson (POB 2 1 58, Yale Station, 
New Haven, CT 06520) is a research 
associate at Yale He has a B.A. from 
Princeton University and a Ph.D. from Yale 
University. His interests are artificial in- 
telligence, software engineering, and computer- 
aided instruction. Dr. }ohnson has been 
pursuing research in artificial intelligence at 
Yale since 1978. 

Elliot Soloway (Department of Computer 
Science, Yale University, New Haven, CT 
06520) is an assistant professor at Yale. He 
has a B.A. in philosophy and a PhD. in com- 
puter science from the University of 
Massachusetts at Amherst. Dr. Soloway 
heads a group at Yale that is exploring the 
cognitive underpinnings of programming. 



APRIL 1985 -BYTE 179 



PROUST 



grammer's intentions assists debug- 
ging, we will present two examples of 
"buggy" programs and discuss why 
alternative approaches to automatic 
debugging fail to identify such bugs. 
Then we will describe how PROUST 
analyzes such programs. Finally we 
will present some statistics showing 
PROUST's performance on large 
numbers of students solutions to a 
typical assignment in an introductory 
programming class. This will help sup- 
port our claim that PROUST's ap- 
proach is adequate for the majority 
of novice programmers' programs. 

Examples of Program Bugs 

Here is a simple programming prob- 
lem called the Averaging Problem: 



Write a program that reads in a se- 
quence of positive numbers, stpp- 
ping when 99999 is read. Compute 
the average of these numbers. Do 
not include the 99999 in the aver- 
age Be sure to reject any input that 
is not positive. 

The student's program must compute 
the average of a series of positive 
numbers. It must ensure that the in- 
put to the program is in fact positive. 
The input terminates when a specific 
value— 99999— is read. Values such as 
this, which signal the end of input, are 
called sentinel values. 

Figure la shows a sample solution 
to the Averaging Problem. This pro- 
gram works except for the following 



(a) 




1 


PROGRAM Average( Input, Output ); 


2 


VAR Sum, Count, Val, Avg: REAL; 


3 


BEGIN 


4 


Sum := 0; 


5 


Count ; = 0; 


6 


Writeln( 'Enter Value:' ); 


7 


Read( Val ); 


8 


WHILE Val <> 99999 DO 


9 


BEGIN 


10 


WHILE Val<=0 DO 


11 


BEGIN 


12 


Writeln( 'Invalid entry, reenter' ); 


13 


Read( Val ); 


14 


END; 


15 


Sum := Sum + Val; 


16 


Count :■ Count+1; 


17 


Writeln( 'Enter value:' ); 


18 


Read( Val ); 


19 


END; 


20 


IF Count >0 THEN 


21 


Write! n( 'No data entered' ) 


22 


ELSE BEGIN 


23 


Avg : m Sum/Count; 


24 


Writeln( 'The average is, 'Avg ); 


25 


END; 


26 


END, 


(b) 




PROUST's output: 


You 


re missing a sentinel test. If a sentinel value is input immediately following a 


nonpositive value, your program will treat it as valid data. 


To see this, try the following data in your program; 


5 


- 5 99999 



Figure 1: {a} One novice programmer's attempt at implementing the Averaging 
Problem, (b) PROUST explains the bug lurking in the program in concise English 
sentences and even offers data illustrating the error. 



bug: if you type 99999 immediately 
after typing a nonpositive value, the 
program will continue to prompt for 
data after the 99999 is read. When 
the program finally does terminate, 
the average will be incorrect. For ex- 
ample, suppose that you input 5,-5, 
99999. Instead of terminating when 
the 99999 is read, the program re- 
quests another input. If the user then 
entered another 99999, the program 
would not print the average as 5, but 
instead would print (5+99999)/2, or 
50002. 

The program interprets 99999 as 
data when the sequence 5, -5, 
99999 is read because when the pro- 
gram reads the -5, it enters the input- 
validation loop, which starts with line 
10, WHILE Val < = DO. This loop 
is intended to iterate until a positive 
value is typed in; 99999 is positive, 
so when the 99999 is read, control 
leaves the input-validation loop. How- 
ever, the program was written with the 
assumption that when the input- 
validation loop is exited, the current 
value of Val is valid input data. In this 
case, Val is not valid data; it is 99999, 
the sentinel value. The loop never- 
theless processes 99999 as if it were 
data. To guard against this case, there 
should be a test for the sentinel after 
the input-validation loop. 

Figure lb is PROUST's output de- 
scribing the missing sentinel-test bug. 
The error is described in two ways: 
First it is described in English; then 
PROUST generates an example of 
data that causes the program to fail. 

Now look at the program in figure 
2a. This is another solution to the 
Averaging Problem, and the bug in 
this program is also fairly obscure. If 
you type a positive value followed by 
a negative value, the negative value 
will be included in the average. Thus 
if you type -2,2, 99999, the average 
will be 2, but if you type 2, -2, 
99999, the average will be 0. 

Unlike the example in listing la, the 
programmer has not left out the sen- 
tinel test but has written the test in the 
form of a WHILE statement instead 
of an IF statement. The student prob- 
ably has a misconception about the 
distinction between the two state- 



180 BYTE • APRIL 1985 



PROUST 



ments and does not understand how 
the control flow in a WHILE loop 
works. As long as the body of the 
loop is straight-line code, the student 
has no problem. However, if the body 
of the loop contains tests, the student 
thinks that the tests should be written 
as WHILE statements to ensure that 
they repeat when the body of the 
loop does. We will refer to this mis- 
conception henceforth as the WHILE- 
for-IF misconception. PROUST's out- 
put for this example, shown in figure 
2 b, takes the misconception into ac- 
count and explains it to the student. 

The bugs in figures la and 2a illus- 
trate the following points. First, bugs 
frequently cannot be detected if you 
don't know what the program is sup- 
posed to do. Both of the programs 
shown run no matter what input is 
read; to determine that there is a bug, 
you must recognize that the programs 
output different results than they 
should. Bugs such as these are not 
unusual; the missing sentinel-test bug 
occurs in 18 percent of novice pro- 
grammers' solutions to the Averaging 
Problem. 

Second, novice programmers need 
help identifying such bugs. These 
bugs cause the programs to fail only 
after unusual inputs— ones that novice 
programmers are unlikely to test. In 
the case of the WHILE-for-IF miscon- 
ception, even if the programmer tests 
the case in question, he or she will 
probably not understand why the pro- 
gram fails because he or she expects 
the WHILE statement to perform a 
different function than it actually 
does. 

Alternatives to 
Intention-based Debugging 

Tb support our claim that debugging 
requires knowledge of the program- 
mer's intentions, we will examine the 
principal alternatives to intention- 
based debugging and show why they 
fall short. The methods we have con- 
sidered are analysis of I/O (input/out- 
put) behavior, analysis of data flow, 
and recognition of patterns of buggy 
code. 

Debugging by analyzing I/O be- 
havior involves determining when the 



(a) 




1 


PROGRAM Average( Input, Output ); 


2 


VAR Sum, Count, Val, Avg: REAL; 


3 


BEGIN 


4 


Sum :« 0; 


5 


Count : = 0; 


6 


Writeln( 'Enter value:' ); 


7 


Read( Val ); 


8 


WHILE Val< > 99999 DO 


9 


BEGIN 


10 


WHILE Val<«0 DO 


11 


BEGIN 


12 


Writeln( Invalid entry, reenter' ); 


13 


Read( Val ); 


14 


END; 


15 


WHILE Val <> 99999 DO 


16 


BEGIN 


17 


Sum := Sum + Val; 


18 


Count := Count +1; 


19 


Whteln( 'Enter value:' ); 


20 


Read( Val ); 


21 


END; 


22 


END; 


23 


IF Count «0 then 


24 


Writeln( 'No data entered' ) 


25 


ELSE BEGIN 


26 


Avg : = Sum/Count; 


27 


Writeln( The average is,Avg ); 


28 


END; 


29 


END 


(b) 




PROUST's output: 


You 


are using a WHILE statement at line 15 where you should have used an IF 


statement. You probably want the code starting at line 15 to execute once each 


time through the loop; your code will make it execute many times. 


The statement in question is: 


WHILE Val<>99999 DO . . . 



Figure 2: (a) Another novice programmer's attempt at implementing the Averaging 
Problem, {b) PROUST once again explains what the problem with the program is, what 
the programmer wanted to do, and what he actually did. 



output of the program is incorrect and 
suggesting bugs that might have 
caused the faulty behavior (see refer- 
ence 2). This approach treats debug- 
ging as similar to medical diagnosis 
(see reference 4). The faulty behavior 
can be thought of as the symptoms 
of the program, and the bugs can be 
thought of as the diseases. There are 
two problems with this approach: A 
program's symptoms cannot always 
be determined, and these symptoms 
cannot always be related to the bugs. 
The bugs in the programs in figures 
la and 2a affect the output of the pro- 
gram only occasionally; recognizing 



when this happens requires knowl- 
edge about what the output should 
look like. Since the WHILE-for-IF ex- 
ample fails to test the input for validi- 
ty after the first positive value is read, 
it appears that this program is miss- 
ing an input-validation test. It is only 
after inspecting the code that it 
becomes clear that the bug is not in 
the input-validation test but in the sen- 
tinel test. 

Another debugging approach you 
might try is data-flow analysis (see 
reference I). This is the approach 
many error-checking compilers use 

{continued) 



APRIL 1985 -BYTE 181 



PROUST 



Data-flow analysis checks for clear 
anomalies in the pattern of data 
definition and for use of data in a pro- 
gram. It can determine when a vari- 
able is defined and never used or 
when a variable is never defined. 
However, if there are no anomalies in 
data flow, data-flow analysis will not 
detect any bugs. Neither example in 
the preceding section has data-flow 
anomalies, so this method would not 
detect the bugs. 

You might also try analyzing the 
structure of the program itself to see 
whether it suggests the presence of 
bugs. You could build a library of 
templates for common bugs, such as 
missing sentinel tests or WHILE 
statements in place of IF statements, 
and then match these templates 
against the program to identify the 
bugs. The problem with this approach 
is that you have no way of knowing 
where to match the bug templates in 
the program. For example, the 
WHILE-for-IF example has three dif- 
ferent WHILE loops. How could you 
tell which WHILE loop really should 
be an IF statement or if any of them 
should be an IF statement? You could 
try to make the bug template more 
specific by making it apply only when 
there are two loops with the same exit 
test, one inside the other. But that 
would make the template too specific; 
it would not apply to other cases 
where WHILE statements appear in- 
stead of IF statements. 

All of these approaches to debug- 
ging attempt to identify bugs without 
any understanding of what the pro- 
gram is supposed to do, and any such 
approach does little more than make 
guesses as to what bug is involved. In 
order to do better, a debugging sys- 
tem has to be able to infer the pro- 
grammer's intentions and relate them 
to the code. 

PROUST'S Approach 

PROUST is written in T, a dialect of 
LISP. The full system contains roughly 
1 5,000 lines of LISP code and runs on 
a VAX-1 1/750. A stripped-down ver- 
sion called Micro-PROUST has been 
developed in conjunction with 
Courseware Inc., of San Diego, Califor- 



MlCRO- 

PROUST FOR 

THE IBM PC 

Micro-PROUST is a subset of the 
larger implementation of 
PROUST It is capable of dealing with 
a limited range of novice programs and 
is currently set up to handle only those 
example solutions to the Averaging 
and Rainfall Problems provided with it. 
Micro-PROUST runs in Gold Hill Com- 
puters Inc. Golden Common LISP on 
an IBM Personal Computer with 5I2K 
bytes of memory. The source code and 
example programs are available for 
downloading from BYTEnet Listings. 
The telephone number is (603) 
924-9820. The file PRSTREAD.ME con- 
tains directions on how to run Micro- 
PROUST 



nia (see the text box "Micro-PROUST 
for the IBM PC" above for more infor- 
mation). Micro-PROUST is capable of 
recognizing the kinds of bugs that are 
described in this article; however, 
there are a variety of tricky bugs that 
PROUST can identify but Micro- 
PROUST cannot. (If you are interested 
in PROUST'S full diagnostic capabili- 
ties, consult reference 3.) 

PROUST's analysis of programs is 
based on knowledge of the program- 
ming problem. Students may solve 
the problem in a variety of ways and 
their programs may have a variety of 
bugs, but they are all trying to solve 
the same problem. Knowledge of the 
problem makes the variability of 
novice solutions more manageable. It 
also provides important information 
about the programmer's intentions. 

To provide PROUST with descrip- 
tions of the programming problems, 
we devised a problem-description 
language We described each problem 
in this language and provided 
PROUST with a library of the descrip- 
tions. Each problem description in 
PROUST's problem-description lan- 
guage is a paraphrase of the English- 
language problem statement that we 



hand out to students. 

To understand the students' pro- 
grams, PROUST also needs to know 
how to solve the problem. Solutions 
to a given programming problem may 
be implemented in a variety of dif- 
ferent ways. Suppose that there was 
only one way to test input for validity 
in a Pascal program, namely, to insert 
a WHILE loop at the top of the main 
loop, such as in figures la and 2a. 
Once PROUST knew that a program 
must validate input, it would know to 
look for such a loop, as well as for the 
sentinel test that must follow. How- 
ever, there are several ways of 
validating input. Listing 1 shows a 
loop that tests input in a different way. 
Instead of there being one input 
validation loop, there are two; one is 
at the bottom of the loop and the 
other precedes the loop. No addi- 
tional sentinel test is required when 
this method is used, because, as soon 
as input is validated, control flows to 
the main exit test of the WHILE loop. 
Therefore, without knowing what 
method the programmer is using for 
validating input, PROUST cannot tell 
whether to look for a sentinel test 
within the body of the loop. In figure 
la it is an error not to have such a sen- 
tinel test, but in listing 1 it is not. 
PROUST needs knowledge about pro- 
gramming so that it can understand 
how each student designed and im- 
plemented his or her solution. Once 
it understands the programmer's in- 
tentions, it can then use knowledge 
about common bugs to identify them 
in the student's program. 

PROUST analyzes programs by syn- 
thesis. When PROUST examines a 
program, it looks up the correspond- 
ing problem description in its library. 
It makes hypotheses about the 
methods programmers may use to 
satisfy each requirement in the prob- 
lem description. Each hypothesis is a 
possible correct implementation of 
the corresponding requirement. If 
one of these hypotheses fits the stu- 
dent's code, then PROUST infers that 
the requirement is implemented cor- 
rectly. If PROUST's hypotheses do not 
fit the student's program, then 
PROUST checks its database of com- 



182 BYTE • APRIL 1985 



PROUST 



mon bugs to see if it can explain the 
discrepancies. 

PROUST'S Problem 
Descriptions 

Problem descriptions in PROUST con- 
sist of programming goals and sets of 
data objects. Programming goals are 
the principal requirements that must 
be satisfied; sets of data objects are 
the data that the program must 
manipulate. 

The first step in translating an 
English-language problem statement 
into PROUST's problem-description 
language is to make the various goals 
that are mentioned in the problem 
statement explicit. Recall that the text 
of the Averaging Problem is the 
following: 

Write a program that reads in a se- 
quence of positive numbers, stop- 
ping when 99999 is read. Compute 
the average of these numbers. Do 
not include the 99999 in the 
average. Be sure to reject any in- 
put that is not positive. 

Solutions to this problem operate on 
a sequence of input data; let us call 
this sequence New. The following 
goals can be extracted from the prob- 
lem statement: 

• Read successive values of New, 
stopping when a sentinel value, 
99999, is read. 

• Make sure that the condition New 
< = is never true. 

• Compute the average of New. 

• Output the average of New. 

We must now take these goals and 
use them to generate a problem 
description for PROUST Each data 
object that the goals refer to is named 
and declared. Each goal extracted 
from the problem statement is re- 
corded in the problem description. 
The resulting problem description is 
shown in figure 3. 

Like all the data structures that we 
discuss in this article, problem 
descriptions are in list notation and 
every statement and expression is 
enclosed in parentheses. The name of 
the program is indicated with a 
Define-Program statement. Objects 



Listing 1; Yet another way to 
implement the input validation for the 
Averaging Problem. 



Read( Val ); 
WHILE Val<=0 DO 
BEGIN 
Writeln( Invalid entry, reenter' ); 
Read( Val ); 
END; 
WHILE Val<>99999 DO 
BEGIN 
Sum := Sum+Val; 
Count ;= Count+1; 
Writeln( 'Enter value:' ); 
Read(.Val ); 
WHILE Val<=0 DO 
BEGIN 
Writeln( Invalid entry, reenter' ); 
Read( Val ); 
END; 
END; 



are named using Define-Object state- 
ments. Goals are indicated using 
Define-Goal statements. 

Object names are preceded by 
question marks. There are two objects 
defined in the Averaging Problem 
description, ?Sentinel and ?New. The 
question-mark notation is used fre- 
quently in artificial-intelligence (AI) 
programs; it indicates that the vari- 
able is not a literal value but is a 
parameter that must be substituted 
when the data structure is used. For 
example the input-data object ?New 
will be substituted with the name of 
the Pascal variable that the student 
uses for storing the input data. The 
object ?Sentinel has the value 99999; 
wherever ?Sentinel appears in the 
problem description it can be sub- 
stituted with 99999. 

Objects can be either constant- 
valued or variable-valued. In this ex- 
ample, ?Sentinel is a constant, with 
the value 99999, and ?New is a 
variable. In PROUST's general prob- 
lem-description language objects can 
have a variety of properties asso- 
ciated with them; however, we will not 
use any such properties in this sim- 
ple example. 



Goal statements consist of a name 
of a type of goal, followed by a list of 
arguments. In the form (Average 
?New) for example, Average is a type 
of goal (to compute an average), and 
?New is the argument of the goal. 
This form requires that the program 
compute the average of ?New. 

Arguments to goal expressions can 
take a variety of forms. They can be 
objects, predicates, or even other goal 
expressions. In the expression (Input- 
Validation ?New (< = ?New 0)), one 
argument is an object (?New), and the 
other is a predicate ?New < = 0. In 
LISP, function names and operators 
precede their arguments, which is why 
the < = precedes the ?New and in 
the expression (< = ). If goals are 
nested, as in (Output (Average 
?New)), the outer goal refers to the 
value computed by the inner goal. 
Thus this goal requires that the pro- 
gram output the average of ?New. 

In this example PROUST's problem 
descriptions are a reasonable approx- 
imation of the original English-lan- 
guage problem statements. These 
problem descriptions describe what 
the programs must do but not how 
they are supposed to do it. PROUST 
must analyze each individual program 
and determine how it is intended to 
satisfy the problem requirements. 

Programming Knowledge 

Programming knowledge in PROUST 
is frame-based (see reference 5). In 
frame-based systems knowledge is 
organized into frames, each of which 
corresponds to a particular concept 
that the system "knows" about. 
Frames are similar to records in rela- 
tional databases, although the opera- 
tions that can be performed on 
frames are somewhat different. 
Knowledge in frames is organized into 
slots, which function as record field 
names, and fillers, which are the 
values assigned to each slot. 

The two kinds of programming 
knowledge that we will consider here 
are goals and plans (other types of 
programming knowledge are dis- 
cussed in reference 6). Goals are 
problem requirements that appear in 

[continued) 



APRIL 1985 • BYTE 183 



PROUST 



problem descriptions. Plans are 
stereotypic methods for implement- 
ing goals. A large part of writing pro- 
grams consists of identifying goals 
that must be satisfied and selecting 
plans to implement these goals, 
Similarly, PROUST retrieves plans 
from its knowledge base for each goal 
referred to in the problem descrip- 
tion. It compares these plans to the 
student's program to determine which 
fits the program best. 

Figure 4 shows PROUST'S definition 
for the Sentinel-Controlled-lnput goal. 
The goal definition contains a series 
of slots: Instanced Form, MainSeg- 
ment etc., together with fillers for 
each of these slots: Read&Process, 



MainLoop:, ?New, etc These slots 
serve various functions, only some of 
which we will discuss here The most 
important slots are the Instances and 
InstanceOf slots. The Instances slot 
lists the various plans in PROUST'S 
knowledge base for implementing this 
goal. This slot's filler is a list of five 
items, each of which is the name of 
a plan. The InstanceOf slot indicates 
the class to which this goal belongs. 
The goal class in this case is Read& 
Process, which is the class of all goals 
that involve reading a sequence of 
values and processing them. 

Figure 5 shows a plan, the Sentinel- 
Process-Read-While plan. This is one 
of the instances of the Sentinel- 



((Define- Prog ram Average) 
(Define-Object ?New) 
(Define-Object ?Sentine! Value 99999) 
(Define-Goal (Sentinel-Controlled-lnput ?New ?Sentinei)) 
(Define-Goal (Input- Validation ?New (< = ?New 0))) 
(Define-Goal (Output (Average ?New)))) 



Figure 3: The Averaging Problem translated into PROUST's problem-description 
language. 



Figure 4: The definition of the goal Sentinel-Controlled-lnput in PROUST's 
problem-description language. 



(Goal- Definition Sentinel-Controlled-lnput 


InstanceOf 


Read&Process 


Form 


(Sentinel-Controlled-lnput ?lnput ?Stop) 


MainSegment 


MainLoop: 


MainVariable 


?New 


NamePhrase 


"sentinel-controlled loop" 


OuterControlPlan 


T 


Instances 


(Sentinel-Process-Read-While 




Sentinel-Read-Process-While 




Sentinel-Read-Process-Repeat 




Sentinel- Process-Read- Repeat 




Bogus-Counter-Controlled-Loop)) 



(Plan-Definition Sentinel-Process-Read-While 


Constants 


(?Stop) 


Variables 


(?lnput) 


Template 


((SUBGOAL (Input ?lnput)) 




(WHILE (<> ?lnput?Stop) 




(BEGIN 
?* 




(SUBGOAL (Input ?lnput)))))) 



Figure 5: A plan for implementing the goal Sentinel-Controlled-lnput 



Controlled-lnput goal. This plan is a 
simplified version of the one PROUST 
actually uses. Plans are also defined 
in terms of slots and fillers. The most 
important slot is the Template slot, 
which describes the form the Pascal 
code implementing this plan should 
take. Plan templates consist of Pascal 
statements, subgoals, and labels. The 
Pascal statements are written in list 
notation rather than ordinary Pascal 
syntax; for example, the form (WHILE 
( < > ?lnput ?Stop) . . .) in Pascal 
syntax would appear as WHILE ?ln- 
put < > ?Stop DO .... Symbols 
that are preceded by question marks 
are pattern variables; these are sub- 
stituted when the plan is used. ?New 
is substituted by a Pascal variable con- 
taining the input data, and ?Stop is 
substituted by a constant, the sentinel 
value. The ?* statement is a "wild 
card" pattern that can be substituted 
by an arbitrary sequence of Pascal 
statements; this is just a placeholder 
in the plan. Subgoals are indicated by 
(SUBGOAL . . .) forms in the tem- 
plate; these are goals that must in turn 
be implemented using other plans. 

Matching Plans 

Let's look at how plans and goals are 
used to understand a program. The 
plan in listing 1 has been imple- 
mented correctly You will see how 
PROUST hypothesizes a plan that the 
program might use and then matches 
this plan against the program. In this 
case the match succeeds because the 
plan is implemented correctly. In the 
next section we will examine what 
happens when plans fail to match 
because the student's code has bugs. 

The first step, before any analysis of 
goals and plans takes place, is to 
parse the student's Pascal program. 
This results in a parse tree. All subse- 
quent analysis of the program is per- 
formed on the parse tree rather than 
on the original program text. 

When PROUST analyzes a program, 
it selects goals from the problem 
description one at a time. Let's sup- 
pose that the goal that is selected first 
is (Sentinel-Controlled-lnput ?New 
?Sentinel). PROUST substitutes any 

{continued) 



184 B YTE • APRIL 1985 




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APRIL 1985 • BYTE 185 



PROUST 



PROUST substitutes 
any objects whose 
values are already 
known into the 
goal expression. 



objects whose values are already 
known into the goal expression. At 
this point the only information avail- 
able about ?New and ?Sentinel is 
what appears in the problem descrip- 
tion. There the value of ?Sentinel is 
listed as 99999, but the value of ?New 
is not listed. Therefore, the value of 
?Sentinel is substituted into the goal 
expression, but ?New is left un- 
changed. The resulting goal expres- 
sion is (Sentinel-Controlled-lnput 
?New 99999). 

PROUST must now retrieve from its 
programming knowledge base plans 
that could be used to implement the 
goal Sentinel-Controlled-lnput It 
retrieves the filler of the Instances slot 
of the definition of Sentinel-Con- 
trolled-lnput shown in figure 4. This 



filler is a list of five items: Sentinel- 
Process-Read-While Sentinel-Read- 
Process-While, Sentinel- Read- 
Process-Repeat Sentinel-Process- 
Read-Repeat and Bogus-Counter- 
Controlled-Loop. Each of these is the 
name of a plan. PROUST selects the 
first plan from the list, Sentinel- 
Process-Read-While. This will be 
PROUST'S initial hypothesis of how 
the program implements the goal 
Sentinel-Controlled-lnput 

Just as known values of objects were 
substituted into the goal expression 
(Sentinel-Controlled-lnput ?New 
?Sentinel), these same substitutions 
must now be performed on the 
selected plan. To see what substitu- 
tions must be made, PROUST ex- 
amines the Form slot of the definition 
of Sentinel-Controlled-lnput (Sentinel- 
Controlled-lnput ?lnput ?Stop). The 
Form slot indicates which pattern-vari- 
able names are used in the plans that 
implement the goal. By comparing 
the Form slot to the goal being 
analyzed, PROUST determines that 
each occurrence of ?lnput in the 
selected plan should be replaced by 
the value of ?New. Each occurrence 
of ?Stop should be replaced by the 
value of ?Sentinel or 99999. Because 
the value of ?New is not known, 



Student's program 

Write) n( 'Enter value:' 
Read( Val ); 



READ PU\N 

(Read Val) 

/♦?New 
Lsentin 
((SUBC 



Val 



WHILE Val <>99999 DO 
BEGIN «i 



WHILE Val<=0 DO 
BEGIN 
Write! n( 'Invalid entry, reenter' ) 
Read( Val ); 
END; 
Sum := Sum + Val; 
Count := Count+1; 
Writeln( 'Enter value:' ); 
Read( Val);^ READ PLAN 

END; 

(Read Val) 



Sentinel-Process-Read-While 

((SUBGOAL (Input ?lnput)) 
(WHILE (< > ?lnput 99999) 
(BEGIN 

?" 

(SUBGOAL (Input ?lnput))))) 



?New = Val 



Figure 6: This shows how the Sentinel-Process-Read-While plan is matched 
against the program in figure 1. 



PROUST simply replaces ?lnput with 
the variable name ?New. PROUST 
assumes that the process of match- 
ing the plan against the program will 
determine what the value of ?New is. 
Figure 6 shows how the Sentinel- 
Process-Read-While plan is matched 
against the program example in figure 
la. Matching starts with the WHILE 
loop. The pattern in the plan for the 
WHILE loop is (WHILE (< > ?New 
99999) . . .). There are two WHILE 
loops in this program: WHILE Val 

< > 99999 DO . . . and WHILE Val 

< = DO .... PROUST tries to 
match each pattern against each of 
these statements. (WHILE (< > 
?New 99999) . . .) matches WHILE 
Val < > 99999 DO . . . , provided 
that Val is substitued for ?New. 
(WHILE (<> ?New 99999) . . .) 
does not match WHILE Val < = DO 
. . . because the statement has a < = 
test instead of a < > test, and 
because it tests against instead of 
99999. Therefore PROUST selects 
WHILE Val < > 99999 DO ... as 
the match for the plan pattern. Since 
Val must be substituted for ?New so 
that the pattern matches, Val is 
recorded as the binding for ?New. 
Afterward, any component of the plan 
that has ?New in it will have Val sub- 
stituted for ?New. 

The next plan component that 
PROUST matches against the program 
is (BEGIN . . .). There are several dif- 
ferent BEGIN statements in the pro- 
gram that could be matched against 
this pattern. However, in the plan tem- 
plate the (BEGIN . . .) pattern ap- 
pears inside of the WHILE pattern 
that was just matched. This means 
that the BEGIN statement that this 
pattern matches must be located in- 
side of the WHILE Val < > 99999 
DO . . . statement. Therefore, there 
is only one BEGIN statement that has 
an appropriate match. 

When PROUST tries to match the 
(SUBGOAL (Input ?New)) com- 
ponents, a different type of process- 
ing is required. These plan com- 
ponents are goals; to match them 
against the program, PROUST must 
go through the same plan-selection 

{continued) 



186 BYTE • APRIL 1985 




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PROUST 



Since PROUST first 
generates a possible 
implementation and 
then matches it 
against the program, 
it is performing 
analysis by synthesis. 



process that it went through in select- 
ing the Sentinel-Process-Read-While 
plan. It first substitutes all pattern 
variables in the goal expression that 
have bindings. Since ?New has Val as 
a binding, the subgoal expression 
becomes (Input Val). PROUST then 
retrieves plans from the plan database 
that implements Input. One such plan 
is the READ PLAN, which employs a 
Pascal Read statement to input the 
value. This plan matches the Read 
statements in the program. 

This example shows how PROUST 
analyzes programs by predicting the 
plans that might be used and then 
testing these predictions. By selecting 
from a range of different plans and 
subplans for each goal PROUST is 
able to generate a variety of different 
ways of implementing each goal. 
Since PROUST first generates a pos- 
sible implementation and then 
matches it against the program, it is 
performing analysis by synthesis. In 
general, generating plan hypotheses 
and matching them against programs 
is rather more complex than the 
scenario presented here; for more in- 
formation, see reference 3. 

Identifying Bugs 

When the Sentinel-Process-Read- 
While plan was matched against the 
program in figure la, the plan 
matched exactly. Since there were no 
match errors, there must not have 
been any bugs in that particular plan. 
It is frequently the case, however, that 
none of the plans that PROUST 



predicts matches the program. When 
this happens PROUST must look for 
bugs that account for the mismatches 
in one of the plans. In this section we 
will discuss one of these mismatches 
in connection with the WHILE-for-IF 
example in figure 2a and show how 
it leads to the discovery of a bug. 

The bug in the WHILE-for-IF exam- 
ple is discovered in processing the 
Input-Validation goal. One of the plans 
that PROUST suggests for implement- 
ing this goal is the so-called Bad In- 
put Loop Test plan. This plan consists 
of a WHILE statement that tests the 
input to see if it is out of range, an 
error message inside the WHILE loop, 
an Input subgoal that rereads the in- 
put if it is out of range, and a test to 
see if the exit condition for the main 
loop has been satisfied. 

Listing 2 illustrates a correct imple- 
mentation of this plan (solving the 
Averaging Problem). 

The Bad Input Loop Test plan 
matches the WHILE-for-IF example of 
figure 2a in all but one respect: there 
is no test for the exit condition of the 
main loop, such as IF Val < > 99999 
THEN .... Where an IF statement 
is expected, a WHILE statement ap- 
pears instead. PROUST has thus en- 
countered a plan difference, i.e., a dif- 
ference between the expected plan 
and the code. When PROUST en- 
counters plan differences it does not 
give up on the plan; instead, it tries 
to find a way of interpreting the plan 
differences as bugs. 

In most cases plan differences are 
explained by means of bug rules. Each 
bug rule has a test part, which ex- 
amines the plan differences to see 
whether the rule is applicable, and an 
action part, which explains the plan 
differences. 

Figure 7 shows the bug rule that is 
invoked to explain the plan dif- 
ferences in the WHILE-for-IF example. 
The rule is written in slot-filler nota- 
tion; one set of slots constitutes the 
test part of the rule, and another set 
constitutes the action part. In the 
WHILE-for-IF rule the test part con- 
sists of a Statement-Type slot and an 
Error-Pattern slot. The Statement- 
Type slot indicates that the plan com- 



188 BYTE • APRIL 1985 



PROUST 



ponent that failed to match the pro- 
gram must be an IF statement. The 
Error-Pattern slot has the value 
(IF . WHILE); this indicates that a 
WHILE statement was found when an 
IF statement was expected. These test 
conditions are both met in the 
WHILE-for-IF example, so the action 
part of the rule is activated. The ac- 
tion part of this rule consists of a Bug 
slot; the filler of this slot is a descrip- 
tion of the bug associated with the 
plan difference. The bug in this 
case is a WHILE-for-IF confusion. 
PROUST's bug analyses of student 
programs consist of bug descriptions 
such as this. When PROUST presents 
its findings to the student, it takes 
each bug description and generates 
an English-language translation for it 
and, if appropriate, generates data il- 
lustrating the presence of the bug. 

Test Results 

PROUST has been tested on large 
numbers of beginners' programs. We 
assigned a class of novice program- 
mers the Rainfall Problem (an elabora- 
tion of the Averaging Problem), which 
is shown in figure 8a. 

We modified the Pascal compiler 
our students were using so that it 
would save copies of every syntac- 
tically correct program that they com- 
piled. This allowed us to examine not 
only the final solution the students 
handed in, but also every inter- 
mediate version of their program. 
Since the first versions are likely to be 
the buggiest, this let us test PROUST 
under the most difficult conditions 
possible. 

Figure 8b shows the results of run- 
ning PROUST on the Rainfall Problem. 
There are 206 different attempted 
solutions to the Rainfall Problem in 
the test set. Of these, PROUST was 
able to derive a complete understand- 
ing of 79 percent of the programs, 
identifying 94 percent of the bugs, a 
)ercentage far higher than people are 
ble to achieve. The chart also in- 
cates that 6 percent of the bugs 
>re not recognized and 55 were 
se alarms. Bugs are counted as not 
ognized if they are either misdiag- 

{continued) 



Listing 2: A correct implementation of the Bad Input Test plan. 

WHILE Va!<=0 DO 
BEGIN 
Writeln( 'Invalid data, please reenter' ); 
Read( Val ); 
END; 
IF Val < > 99999 THEN 



(Define-Rule WHILE-for-IF 
Statement-Type IF 
Error-Pattern (IF . WHILE) 

Bug (WHILE-for-IF Confusion (FoundStmt ,*MRet*) 

(Histlnst ,*HistoryNode*))) 



Figure 7: The WHILE-/or-IF bug rule invoked by PROUST to explain the plan 
difference between the faulty part of the program of figure 1 and the correct 
implementation of this part in listing 1. 



m 

Write a Pascal program that will prompt the user to input numbers from the terminal; 
each input stands for the amount of rainfall in New Haven for a day. Note: Since rainfall 
cannot be negative, the program should reject negative input. Your program should 
compute the following statistics from this data: 

1. the average rainfall per day 

2. the number of rainy days 

3. the number of valid inputs (excluding any invalid data that might have been read in) 

4. the maximum amount of rain that fell on any one day 

The program should read data until the user types 99999; this is a sentinel value signal- 
ing the end of input Do not include the 99999 in the calculations. Assume that if the 
input value is nonnegafive, and not equal to 99999, then it is valid input data. 



(b) 



Total number of programs: 


206 




Number of programs with bugs: 


183 


(89 percent) 


Number of programs receiving full analyses: 


161 


(79 percent) 


Total number of bugs: 


570 




Bugs recognized correctly: 


533 


(94 percent) 


Bugs not recognized: 


29 


(6 percent) 


False alarms: 


55 




Number of programs receiving partial analyses: 


35 


(17 percent) 


Total number of bugs: 


191 




Bugs recognized correctly: 


71 


(37 percent) 


Bugs deleted from analysis: 


70 


(37 percent 


Bugs not recognized: 


50 


(26 percent) 


False alarms: 


19 





Number of programs PROUST did not analyze: 



9 (4 percent) 



Figure 8: (a) The Rainfall Problem was assigned to a class of novice programmers to 
test the effectiveness of PROUST (b) This shows the results of running PROUST on 
the Rainfall Problem. 



APRIL 1985 -BYTE 189 



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PROUST 



Ultimately, PROUST 
will be incorporated 
into a programming 
curriculum for students. 



nosed or missed entirely. Bugs are 
counted as false alarms if they are 
either not present in the program or 
if they are present but misdiagnosed. 
Consequently, misdiagnosed bugs are 
counted both as false alarms and as 
not recognized, which inflates the 
total number of diagnosis errors. 

When PROUST fails to understand 
a program completely its ability to 
recognize bugs deteriorates; 17 per- 
cent of the programs were analyzed 
partially. In such cases PROUST 
deleted from its bug descriptions 
those bug analyses that were ques- 
tionable, given that the program was 
only partially understood. The bug 
descriptions that remained were fre- 
quently wrong, but at least PROUST 
was able to warn the student to take 
the analysis with a grain of salt. The 
remaining 4 percent of the programs 
deviated from PROUST'S expectations 
so drastically it could not analyze 
them at all. In these cases no bug 
report was generated. 

We are not yet sufficiently satisfied 
with PROUST's accuracy to make it 
generally available to students. The 
false-alarm rate should be lower, and 
the fraction of programs that PROUST 
analyzes completely should be higher. 
When part of a program cannot be 
analyzed, PROUST should try to 
determine why that part of the pro- 
gram cannot be analyzed and try to 
account for the unanalyzed code. 
Once this is done we expect PROUST 
to succeed on 80 to 85 percent of the 
programs it analyzes. At that stage we 
will make it available to students on 
line. 

Conclusion 

PROUST is capable of high-quality 
analysis of bugs in novice programs. 



It is almost at the level where it could 
be incorporated into a programming 
curriculum and provide significant 
benefits to students. Here we have 
given a simplified view of how 
PROUST finds bugs. The next step is 
to build an automated programming 
course around PROUST. Such a 
system would not only correct stu- 
dents' mistakes but would also sug- 
gest additional problems for the stu- 
dents to solve to give them practice 
where they need it. ■ 



AUTHORS' NOTE 

This work was cosponsored by the Person- 
nel and Training Research Groups, Psycho- 
logical Sciences Division, Office of Naval 
Research, and the Army Research Institute 
for the Behaviorial and Social Sciences, 
under Contract Number N00014-82-K- 
0714, Contract Authority Identification 
Number Nr 154-492. 

Additional papers dealing with bug 
classification, automatic debugging, and 
the cognitive underpinnings of program- 
ming can be obtained by writing to the 
following address; Cognition and Pro- 
gramming Project, Department of Com- 
puter Science, Yale University, POB 2158 
Yale Station, New Haven, CT 06520. 

Special thanks to Greg Kearsley and 
Leszek Izdebski of Courseware Inc. and 
Bret Wallach of Advanced Processing for 
their efforts in developing Micro-PROUST. 



REFERENCES 

1. Fosdick, L. D, and L. J. Osterweil. "Data 
Flow Analysis in Software Reliability." Com- 
puting Surveys 8, vol. 3, 1976, pages 
305-330. 

2. Harandi. ML T. "Knowledge-Based Pro- 
gram Debugging: A Heuristic Model." Pro- 
ceedings of the 1983 SOFTFAIR. 

3. Wertz, H. "Stereotyped Program Debug- 
ging: An Aid for Novice Programmers." In- 
ternational journal of Man-Machine Studies 16, 
1982, pages 379-392. 

4. Shortliffe, E. H. Computer-Eased Medical 
Consultations: MYCIN. New York: American 
Elsevier Publishing Co., 1976. 

5. Minsky, M. "A Framework for Represent- 
ing Knowledge." The Psychology of Computer 
Vision, P. Winston, ed. New York: McGraw- 
Hill, 1975. 

6. Johnson, W. L. "Intention-Based Diag- 
nosis of Programming Errors." Yale Univer- 
sity Department of Computer Science 
1984. 



190 BYTE • APRIL 1985 




i i i i H 




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192 BYTE • APRIL 1985 



ARTIFICIAL INTELLIGENCE 



ARCHITECTURES 

FORM 



AS ARTIFICIAL-INTELLIGENCE soft- 
ware grows in complexity and as AI 
applications move from laboratories 
to the real world, computational 
throughput and cost are increasingly 
important concerns. 

In general, there are two motives for 
increasing the efficiency of computa- 
tions. One is the need to obtain faster 
computation, regardless of cost. This 
may be due to explicit real-time con- 
straints or to current methods being 
taxed well beyond the limit of com- 
plexity or timely response. The other 
motive seeks to obtain a better cost/ 
performance ratio. Behind both, how- 
ever, is usually the imperative of real- 
world market pressures. 

Opportunities for increased efficien- 
cy in AI computations exist at every 
level. Improved instruction-set designs 
combined with improved AI language 
semantics allow more powerful com- 
piler optimization. Concurrent ma- 
chines allow parallel execution of LISP 
and declarative constructs, raising 
issues of and, or, and stream parallelism. 
Custom VLSI (very-large-scale integra- 
tion) hardware for current AI perfor- 
mance bottlenecks includes devices 
such as hardware unifiers, associative 
memory, and communication hard- 



by Michael F. Deering 

Hardware and software 
for efficient processing 



ware for coordinating parallel search- 
es. Many of these speedups are or- 
thogonal and can potentially increase 
performance by several orders of 
magnitude. However, this is not always 
the case; some language optimiza- 
tions have a tendency to serialize 
computation, thereby negating the 
gains of parallelism. 

As part of an effort to design a 
massively concurrent architecture for 
AI computation (the Fairchild FAIM-1 
project— see the text box on page 
202), this article examines several 
potential throughput increases and 
their interactions. 

Misconceptions 

There are several misconceptions 
about what needs to be done to im- 
prove computational throughput for 
AI. Since most AI programming is 
done in LISP, many researchers 
believe the key is simply to make LISP 
faster. However, this approach ignores 
other, easily obtainable potential 
speedups. 

Other computer scientists see no 
reason to concentrate on anything 
other than the fundamental problem 
of parallelism, an approach that 
presumes a routine solution of a very 



difficult problem: decomposing ar- 
bitrary AI computations to effective- 
ly use thousands of parallel proces- 
sors. A problem with this approach is 
that most programs, even ones with 
a high degree of inherent parallelism, 
almost always have several serial bot- 
tlenecks. As an example most parallel 
programs need to gather the result of 
one batch of parallel computations 
for reflection before generating the 
next batch. In many cases, these serial 
processes dominate the running time 
of the entire program. So you cannot 
ignore the issue of how to extract as 
much serial speed as possible from 
languages and machines. Otherwise, 
once you've built an expensive paral- 
lel machine hundreds of times faster 
than existing machines, a new com- 
piler or microcode might make some 
existing serial machines even faster. 
The machine coded unifier in the 
Crystal AI language for instance is 
two orders of magnitude faster than 
the LISP-coded unifier in the pre- 

icontinued} 

Michael F. Deering is a computer scientist with 
the Computer-hided Systems laboratory. He 
can be reached through Schlumberger Palo 
Alto Research. 3340 Hillview Ave., Palo 
Alto, CA 94304. 



APRIL 1985 • BYTE 193 



ARCHITECTURES 



decessor PEARL AI language (see ref- 
erence 3). 

Software Improvements 

One way to improve AI language im- 
plementations would be to compile 
the language directly to machine 
code. Most AI languages" are not 
computer languages but packages of 
routines on top of an existing lan- 
guage, usually LISP. While this is a 
great way of rapidly prototyping a lan- 
guage and results in considerable sav- 
ings in development costs over a tra- 
ditional full compiler, it does not lead 
to very efficient implementations. If 
increasing the speed of AI applica- 
tions leads to the extreme of build- 
ing custom parallel processors, it is 
silly not to compile AI languages 
directly onto these processors. There 
is a large body of computer science 
knowledge on compilation that can 
be brought to bear, and great poten- 
tial for performance increases. (Con- 
sider the lOOtimes plus speed differ- 
ence between most LISP-based Pro- 
log interpreters and Warren's DEC-20 
Prolog compiler— see reference 17.) 
Make sure that the language is com- 
pilable. Because most AI languages 
have been interpreted, issues of com- 
pilability generally have not been 
thought through. Language features 
that seemed efficient in an interpreted 
environment may be very slow when 
compiled, if they are compilable at all. 



A proper choice of features in light of 
a compiled environment leads to 
more efficient program execution. 

Another problem with many AI lan- 
guages is the lack of general tools to 
support common applications. While 
it can be argued that this allows users 
to write their own customized tools 
(which may be very efficient), most 
users will do a much worse job than 
the language implementor could. For 
example, PEARL did not directly sup- 
port any particular theorem-proving 
or search system (such as forward and 
backward chaining), leaving users to 
their own devices. But the MRS sys- 
tem (reference 11), while providing a 
convenient meta-level control for 
users to write their own search sys- 
tems, also provides a range of built- 
in search strategies, from backward 
chaining to full-resolution theorem 
proving. An extensive library of well- 
written routines of general use speeds 
the operation of typical user pro- 
grams (not to mention their devel- 
opment). 

Hardware Considerations 

It is often claimed that conventional 
computer instruction sets are not well 
suited for AI software, but there have 
been few attempts to quantify the 
reasons why. For older-generation 
machines, you can easily point to 
severe address-space limitations and 
the lack of flexible pointer- 



Table I: The timing results of the aggregate function too for three LISP 
implementations on six different processors. 

LISPs vs. Processors on 
(defun foo(x)(+(car x)(cdr x))) 


Machine 


Zetalisp 


Franz LISP 


PSL 


VAX 


53.8 ^s 


13.9 ms 


5.6 

MS 


68000 


65.2 /is 


43.6 ms 


5.8 

MS 


68010 


68.6 mS 


43.6 mS 


10.6 
MS 


68020 


16.1 M s 


19.9 ms 


3.1 

MS 


MIT CADR 


19.0 mS 


n/a 


n/a 


3600 


6.4 mS 


n/a 


n/a 



manipulation facilities (reference 6). 
But what of the new, modern 
machines, such as the DEC VAX, 
Motorola 68000, National Semi- 
conductor 16000, and various RISC 
(reduced instruction set computer) 
machines— how do they compare with 
the custom LISP machines (references 
13 and 15)? lb obtain insights into 
instruction-set design, I examined 
several LISP systems and the fine 
details of their implementation 
(reference 5). 1 learned, among other 
things, that it is very important to 
identify how rich an environment you 
wish to support. For example con- 
trary to many people's expectations, 
on a large application program Franz 
LISP (reference 8) on a DEC VAX-11/ 
780 was not significantly slower than 
Zetalisp on a Symbolics 3600. The dif- 
ference was that nearly all type- 
checking and generic-function 
capabilities were either turned off (by 
the programmer) or missing in Franz 
LISP, where the overall environment 
was much poorer. Assuming that such 
features are not frills, I also examined 
the expense of providing them on dif- 
ferent architectures. 

Flexible LISP processing depends 
on dynamic type checking and 
generic operations. Associating the 
data type directly with the data ob- 
ject means that the data type will 
always be at hand during processing, 
and this is the reason that tagged 
memory architectures are well suited 
to LISP processing. Because of this 
association, the speed of various pro- 
cessors on the generic LISP task 
depends on how fast the processors 
can effectively emulate a tagged- 
memory architecture. 

I performed a number of experi- 
ments to compare LISP systems on 
different processor instruction sets. As 
a representative sample, table 1 
shows the timing results for a simple 
aggregate function incorporating 
some of the most common LISP 
primitives— CAR, CDR, plus, and 
function call/return. 

More extensive benchmarks have 
borne out roughly the same speed 
ratios. Not unexpectedly the variance 

[continued) 



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APRIL 1985 • BYTE 195 



ARCHITECTURES 



Listing 1: MC68010 assembly-language code for the LISP function CAR. The 
code in boxes can be replaced by enhancements to the instruction set to decrease 
the code's execution time. 



Zetalisp car for 68010 



To take the car we do a few lines of in line code and 
;then index jump to a subroutine. (Space for time.) 
The cons cell to take the car of is assumed in aO. 



;dispatch to CAR subr based upon the tag in upper bits of aO 
4 movel a0,d2 ;put a copy of the arg into d2 

24 Isll #8,d2 ;firsl 8 of: shift copy over by 9 bits 



10 


Isll #1,d2 


;last 1 of: shift copy over by 9 bits 


14 


andl #0x1F0,d2 


;and off non-tag (shifted over) 


4 


movel d2,a2 


;need tag in A-reg for dispatch 


18 


jsr CAR(a2) 


: branch to car table indexed by type 




;At return, the car 


of the object is in a2 



;The CAR subroutine. 

CAR + DTP-CONS: ;CAR procedure entry point 

;for nornal cons cell. 
;We will arrive here if the argument passed to car was of type 
; "pointer to cons cell". Other objects passed to car = > error 



;follow the point to the car 
4 moveal a0,d2 



;put a copy of the arg into d2 



14 


andl #0xFFFFFF,d2 


;and off tag 


4 


moveal d2,a2 


;put d2 into an address register 


12 


moveal (a2),a2 


;follow the car pointer. 



;dispatch to TRANSPORT subr based upon the tag 
; in the upper bits of a2 

4 movel a2,d2 ;put a copy into d2 

24 Isll #8,d2 ;first 8 of: shift copy over by 9 bits 



{continued) 



exceeded 50 percent. Slight modifica- 
tions of the compilers or instruction 
sets produced similarly large changes 
in the speeds. 

Existing Franz LISP and PSL (refer- 
ence 12) compilers for the DEC VAX 
and Motorola 68000 were used to 
compile too. Type checking was 
turned off to obtain the fastest 
speeds. (Both PSL and Franz LISP 
were told not to verify that the argu- 
ments of + were small integers; Franz 
LISP did and PSL did not check for 
numeric overflow.) The timing figures 
were generated by examination of the 
assembly code produced and some 
actual machine timings. The timings 
of Zetalisp for the 3600 and CADR 
were taken by running existing sys- 
tems. Zetalisp-like operations for the 
DEC VAX and Motorola 68000s were 
hand-coded, and the timings were 
produced in the same way as those 
for PSL and Franz LISP. The 68000 
and 68010 were 10-MHz, no-wait-state 
machines. The 68000 used 24-bit ad- 
dresses, leaving the upper 8 data bits 
free for tag values. The 68010 used 
32-bit addresses and required 
removal of the tag bits with an AND 
operation before addresses could be 
used. The 68020 timings are 
estimates based upon the best "cache 
case" timings in the 68020 data book 
and are not as accurate as the timings 
for the other machines. The 68020 is 
assumed to be running at 16 MHz 
with an external 16K-byte memory 
cache and memory-management unit 
(MMU), giving a memory-access time 
of 185 nanoseconds. (The 68020 has 
an additional small instruction cache 
on board.) 

Other experiments examined the ar- 
chitectural requirements for fast com- 
putation of some AI operations not 
directly supported by LISP, in par- 
ticular unification and associative 
search. When AI languages are fully 
compiled, these two functions often 
become the computational bottle- 
necks. For traditional microprocessor 
instruction sets, the requirements of 
these operations turned out to be the 
same as for LISP primitives; fast 
simulation of tagged architectures. 
More specifically, the instructions and 



196 BYTE • APRIL 1985 



ARCHITECTURES 



capabilities that would make a con- 
ventional microprocessor better 
suited for LISP (along with Prolog, 
Krypton, MRS, PEARL, etc.) are 

• "Extract bit field and dispatch": an 
instruction to extract a sequence of 
bits from an operand, then add these 
bits to a dispatch table address, and 
jump indirect. This is necessary for 
rapid handling of tag values in generic 
operations, type checking, and for 
helping with unification. 

• "Extract two bit fields, concatenate, 
and dispatch": an instruction for 
dispatching on the context of two 
operands (needed for the same 
reason as the one-argument version). 

• The memory address system of the 
processor should ignore the upper 
address bits of data addresses that 
are not otherwise in use. This allows 
the wasted space in 3 2 -bit pointers to 
be used as a tag field. 

In the Zetalisp-like code, more than 
30 percent of the time on the 68000s 
was spent in emulating the bit-field 
dispatch instructions. Stripping off the 
tag bits accounted for approximately 
another 10 percent. It is therefore 
estimated that if the existing micro- 
processors had hardware support for 
these features, full type-checking 
LISPs (like Zetalisp) could run almost 
twice as fast. These percentages come 
from hand-implementing several Zeta- 
lisp primitives on current micropro- 
cessors. As an example, listing 1 
shows the 68010 assembly language 
code for CAR. The number of pro- 
cessor clock cycles per instruction is 
shown in the left-hand column. The 
boxed code can be replaced by a 
single instruction (see listing 2). 

Listing 2 shows CAR for the 68010 
recoded, assuming two architectural 
refinements. First, assume that the up- 
per 7 bits of all addresses are ignored 
by the virtual-memory system. Sec- 
ond, assume one additional instruc- 
tion, "extract bit field and dispatch." 
This instruction takes the bit field out 
of the second argument, as specified 
by the first argument (format: 
< #starting-bit. field-width >), adds it 
to the third argument (the jump-table 

{continued) 











10 Isll #1,d2 ;last 1 of: shift copy over by 9 bits 






14 andl #0x1F0,d2 ;and off non-tag (shifted over) 






4 move! d2,a3 ;need tag in A-reg for dispatch 






10 jmp TRANSPORT(a3) ;branch to car table 






; indexed by type. 






The reason for this jump is to check 






;for possible invisible pointers, unbound, etc. 






TRANSPORT + NORMAL: ;jump entry point for normal 




;cons cell contents 


8 rts ; We're all done, return 


182 clocks, @10MHz = 18.2/iS 



Listing 2: The modified listing l code, incorporating architectural refinements to 
the processor's instruction set. 

;Now the car routine is recoded using the new instructions: 

;index jump to a subroutine. 

; dispatch to CAR subr based upon the tag in upper bits of aO 

22 extract-dispatch <#26,#6>,aO,CAR 
;The CAR subroutine. 

CAR + DTP-CONS: ;CAR procedure entry point for 

; normal cons cell. 
; follow the pointer to the car 

12 moveal (a0),a2 ;the upper 6 bits of aO are ignored. 
; dispatch to TRANSPORT subr based upon the tag 
;in the upper bits of a2 

22 extract-dispatch <#26,#6>,a2, DISPATCH 
TRANSPORT + NORMAL: ;jump entry point for normal 
;cons cell contents 
8 rts ;We're all done, return 



64 clocks, @10MHz =6.4^s, 2.8 times faster 



APRIL I985 -BYTE 197 



ARCHITECTURES 



base address), and indirectly jumps 
through this address. (The 68020 has 
a fast bit-field extraction instruction. 
This accounts for much of its in- 
creased speed over the older 68000 
on the LISP task in table 1.) 

For new, fully custom machine de- 
signs that are tailored specifically for 
AI, such features can all be built in. 



With a tagged architecture, many 
generic operations, such as add, do 
not need to be dispatch subroutine 
calls. Rather, the processor can ex- 
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add instruction and, if they are sim- 
ple integers, directly perform the add. 
If the arguments are of a more exotic 
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generate a software interrupt to an 
appropriate routine. Further, for such 
designs it is very helpful to have a 
"smart" memory subsystem capable 
of rapidly chasing down indirect 
pointers as on the DEC PDP-10 and 
the custom LISP machines. Additional 
customization of an AI instruction-set 
design generally falls into the 
category of complete, attached co- 
processors rather than just additional 
instructions. This tactic has already 
been taken by many microprocessors 
whose floating-point instructions are 
handled by what could be viewed as 
attached coprocessors. The specific 
categories of important attached co- 
processors include pipelined unifiers, 
associative-memory subsystems, mul- 
tiprocessor communication packet 
switchers, and special signal-pro- 
cessing chips for vision and speech. 
Studies of a custom instruction set 
for the FAIM-1 machine indicate that 
not only can a single processor be de- 
signed that is memory-bound by 
DRAM (dynamic random-access read/ 
write memory) access delays but that 
this is the case even when a large 
cache is employed. This is an impor- 
tant fact. It means that parallel 
machines sharing a single large com- 
mon memory are a bad idea because 
there isn't enough memory band- 
width to go around. 

Parallelism: The Great Hope 

Traditional views cite concurrency as 
a great method of obtaining increased 
computational power. In practice 
however, designers continue to con- 
centrate on making faster and faster 
single-processor machines. Now that 
hard technological limits have been 
reached for serial processors, paral- 
lelism has become recognized as 
perhaps the only hope for further per- 
formance increases. Unfortunately, 
concurrency is not free— it brings new 
systems organization problems to the 
fore. 

The first conceptual problem with 
parallelism is the confusion between 
multiprocess/^ and multiprocessors. There 
are algorithms that very elegantly ex- 
press a set of cooperating processes 

{continued) 



198 BYTE • APRIL 1985 



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(e.g., writers and readers), but these 
same algorithms have little or no in- 
herent parallelism that can be ex- 
ploited by parallel computers. Just 
because an algorithm can be ex- 
pressed in concurrent terms is no 
guarantee that, when run on many 
parallel processors, it will run 
significantly faster than as separate 
processes on a single sequential 
machine. 

The true measure of parallelism is 
how much faster a given program will 
run on n simple parallel processors 
compared to how fast it would run on 
a single simple processor and for 
what ranges of n this is valid. The best 
you can hope for in principle is a fac- 
tor of n speedup, but in practice this 
is rarely reached (due to overhead 
and communication contention). The 
maximum amount of speedup at- 
tained for a given program using any 
number of parallel processors in- 
dicates the inherent parallelism of 
that program. Unfortunately, for most 
existing programs written in tradi- 
tional computer languages, the max- 
imum parallelism seems to be about 
a four-times speedup (reference 10). 
This surprisingly low number is due 
to the style of programming enforced 
by the traditional languages. There 
are special-purpose exceptions to this 
rule and the hope is that nontradi- 
tional parallel languages will en- 
courage more concurrent algorithms. 
Compilers for parallel machines can 
take advantage of techniques such as 
and, or, and stream parallelism if AI 
languages support the concurrent 
control structures that give rise to 
them. But the jury is still out as to the 
amount of speedup such techniques 
can deliver. 

Another problem in parallelism is 
failure to take the entire systems con- 
text into account. Before building a 
parallel machine, you must not only 
simulate the machine but determine 
how to write large programs for it. 
This reveals potential flaws in the 
machine before commencing with 
time-consuming hardware develop- 
ment. The simulation must properly 
take scheduling and technologically 
realistic hardware-communication 



overhead into account or the timings 
produced will have little or no connec- 
tion to reality. 

Good examples of software systems 
that have not taken realistic hardware 
considerations into account are some 
of the parallel LISPs that have been 
proposed (reference 9). These pro- 
posals point out places in LISP-like 
processing where multiple processors 
could be exploited, but they do not 
analyze the overheads incurred. They 
usually assume that multiple pro- 
cessors share a single large main 
memory where CONS cells and other 
LISP objects are being stored. This is 
the equivalent of assuming that 
memory is infinitely fast, which is just 
as unrealistic as assuming that pro- 
cessors are infinitely fast. The prob- 
lem is that with current technology a 
single well-designed LISP processor 
could run faster than current mass- 
memory technology could service it. 
Adding processors would thus not 
result in any increase in through- 
put. 

There are several reasons why 
designers of parallel LISPs may have 
missed this fact. Perhaps one is that 
current 68000 LISPs are not memory- 
bound. Another is the potential use 
of caches to reduce the required 
memory bandwidth to each pro- 
cessor. However, even with caching, 
the number of processors that can be 
added is not unlimited; a 90 percent 
hit-rate cache would accommodate 
only 10 processors. 

What about the thousand-processor 
architectures envisioned? Experimen- 
tal data shows that a single processor 
can run significantly faster than mem- 
ory can service it: You must employ 
a cache just to keep a single pro- 
cessor running full tilt. The lesson is 
that processors are still much faster 
than memories, and any sharing of 
data between multiple processors 
(beyond a few) must be done with 
special communication channels. In 
other words, MIMD (multiple instruc- 
tion, multiple data) machines with a 
single shared memory are a bad 
parallel architecture. This has impor- 
tant implications for some AI 
paradigms, such as Blackboard sys- 



200 B YTE • APRIL I985 



ARCHITECTURES 



terns and Production systems that (in 
their current form) rely on memory for 
communication between tasks. 

This is not to say that there are no 
opportunities for spreading LISP-Iike 
processing across hundreds of pro- 
cessors. There are many techniques 
other than a single shared-memory 
system for connecting processors. 
More realistic areas of research in- 
clude the spreading of parallel in- 
ference computation via techniques 
of and, or, and stream parallelism. The 
point is that all of these techniques 
incur some overhead and you cannot 
simply solve the parallel-computation 
problem by saying that arguments to 
functions should be evaluated in 
parallel. You must first study hardware 
technology to determine at what grain 
sizes parallelism is feasible and then 
figure out how to make Al-language 
compilers decompose programs into 
the appropriate-size pieces. 

Custom VLSI 

One of the principal hopes for more 
efficient future computation is the use 
of custom VLSI hardware to ac- 
celerate particular functions. The ideal 
functions for silicon implementation 
should be current bottlenecks in AI 
systems and generic to many AI tasks. 
Four of the most important classes of 



operations that fit this description are 
symbolic matching of abstract objects, 
semantic associative memory, paral- 
lel-processor communication, and 
signal-to-symbol processing, 

Matching and Fetching 

Matching two objects is a general and 
pervasive operation. Most AI lan- 
guages define one or more match func- 
tions on their structured data types 
(such as frames). Some of these 
match functions are very ad hoc (thus 
supposedly flexible), but others are 
subsets or supersets of unification. If 
significant support for matching is to 
be provided in hardware, the match 
function must have well-defined 
semantics. 

Al-language objects can be com- 
plexly structured and used to repre- 
sent semantic knowledge. The objects 
can contain embedded pattern- 
matching variables that are given 
bindings as a side effect of the match 
operation. Thus the matching of these 
objects is complex. To give the flavor 
of the matching process, I'll present 
a short description of the unification 
matching function. (For a more exact 
description, see any good description 
of the Prolog language.) Matching is 
best described by recursively defining 
the semantics of the match operation: 



1. If the two objects to be matched 
are structured (nonscalar) objects, 
recursively match their subcom- 
ponents (or "slots"). The two objects 
are said to match if and only if all 
pairs of slots match. Otherwise, the 
objects do not match, and any side ef- 
fects of the matching process must be 
undone. 

2. If the two objects to be matched 
are scalar objects (integers, floating- 
point numbers, atoms, symbols, char- 
acters, etc.), then the match function 
reduces to simple equality. 

3. If one of the two objects to be 
matched is a pattern-matching vari- 
able, the match operation must check 
the variable's binding state. If the 
variable already has been bound to 
a value, the match operation con- 
tinues using the value in place of the 
variable. If the variable has no current 
binding, it is bound to the value of the 
object against which it was being 
matched, and the match succeeds. 

4. If both of the objects to be 
matched are unbound pattern- 
matching variables, then one is bound 
to the other as a placeholder for 
possible future bindings. If either 
variable is later bound to a "real" 
value, then both variables will be 
bound to this value. 

{continued) 



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APRIL I985 -BYTE 



ARCHITECTURES 



The match operation produces a 
binary result: Did the two objects 
match successfully or not? Successful 
matches produce the bindings of 
pattern-matching variables necessary 
to make the two objects identical in 
as general a way as possible. 

Many AI languages augment this 
match operation with checks for cir- 
cularity in the list structure (the "oc- 
cure check"), segment matches 
(similar to Snobol's), and the matching 
of sets and bags. 

When a match function is applied 



to a database of objects, the opera- 
tion is called fetching. In this case 
matching becomes the inner loop 
operation, and this is a context in 
which matching should be optimized. 
An ideal solution would integrate 
matching circuitry with memory cir- 
cuitry so that fetching would become 
a memory access of a content- 
addressable memory (CAM). The 
choice of match function is critical. Tb 
obtain reasonable memory densities, 
the relative silicon area of match cir- 
cuitry cannot overwhelm that of the 



memory circuitry. Unfortunately full 
unification and more complex match 
functions require too much circuitry 
to be built into memory cells. But if 
a formal subset of unification could 
be built in, then the CAM could act 
as a prefilter function for unification. 
The primary source of unification 
complexity is the maintenance of the 
binding environment. The match func- 
tion of mock unification resembles full 
unification except that all variables are 
treated as "don't cares" and no bind- 

{continued) 



FAIM-1 Project Overview 



Our goal is to produce a high-per- 
formance symbolic multiprocessor, 100 
or more times faster than current 
machines in common use (e.g., the DEC 
VAX- 11/780) to meet the voracious 
computational demands of future arti- 
ficial-intelligence applications. 

The FA1M-1 (Fairchild Artificial In- 
telligence Machine) is a multiprocessor 
system consisting of a number of iden- 
tical processing elements called hec- 
tagons interconnected by a communica- 
tion network. Each hectagon is a com- 
plete computer capable of sequentially 
executing a compiled program that is 
stored in its local memory. Hectagons 
communicate with each other via mes- 
sages that are sent through communi- 
cation ports. A hectagon has six ports 
that may be active concurrently. 

The FAIM-I architecture permits the 
connection of arbitrary numbers of 
hectagon processing elements in a 
hexagonal-mesh topology. The ensem- 
ble of hectagons is capable of exploit- 
ing very large levels of concurrent 
multiprocessing and as such should 
provide an extremely attractive target 
machine for future concurrent AI ap- 
plications due to its performance. 
Moreover, each individual hectagon is 
itself a concurrent processor com- 
posed of six modular sybsystems, each 
of which provides an important level 
of support for symbolic computation. 

A hectagon is composed of six self- 
timed subsystems named FRISC, 
SRAM. ISM. CxAM. SPUN, and Post 
Office. Three of these subsystems (ISM, 
CxAM, and SRAM) are specialized 



memory systems that provide "in- 
telligent" storage, while the other 
systems support inter-hectagon com- 
munication (Post Office), processing 
(FRISC), and unification (SPUN). 

FRISC: The "fanatically reduced in- 
struction set computer" component of 
the hectagon corresponds to the cen- 
tral processing unit in a conventional 
computer. It is a stack-oriented ma- 
chine with a 20-bit word composed of 
a 16-bit data field and 4-bit tag field. 
Tag bits and associated tag-handling 
hardware support generic operations. 
SRAM: The FRISC views most data 
structures as objects: a conventional 
memory with a small finite-state ma- 
chine attached to it (collectively called 
the SRAM) provides an object-oriented 
memory system for the FRISC For ex- 
ample, using the data tag bits the 
SRAM can chase a pointer chain to 
retrieve an object requested by the 
FRISC. 

ISM: The "instruction stream memory" 
subsystem delivers instructions to the 
processor at high speed. Thus, the nor- 
mal address calculation activities that 
have traditionally been the processor's 
responsibility are the ISM's job. 
CxAM: The "context-addressable 
memory" subsystem provides direct 
hardware support for important pat- 
tern-matching functions inherent in 
symbolic programs. The structure of 
both entries and queries in the CxAM 
is an S-expression. Therefore, each slot 
can either be a structure or an atom. 
Atoms can be symbols, numbers, vari- 



ables, or don't cares. The CxAM re- 
sponds to four commands: Find Match. 
Give Match, Delete Structure, and Add 
Structure. The CxAM manages its own 
free space and removes garbage auto- 
matically. 

SPUN: The "streamed pipeline unifier" 
supplies direct hardware support for 
logic programming. The CxAM finds 
the next rule or set of rules to be tried 
but does not perform full unification 
since its match function does not con- 
sider variable bindings. The SPUN unit 
takes the query and the streamed set 
of matched structures, detects which 
variables still need to be matched, 
fetches the binding in the current con- 
text from the SRAM, and completes 
the unification. This may entail binding 
a variable, in which case the SPUN unit 
must post this binding back in the 
SRAM. More complex structure manip- 
ulation requires the SPUN to interrupt 
the FRISC for services. 
Post Office: Hectagons communicate 
by sending messages to each other; it 
is the duty of the Post Office to pro- 
vide autonomous communication sup- 
port for its hectagon. If a message's 
destination is not one of the sender's 
six neighboring hectagons, the Post Of- 
fice will route the message to its 
destination by sending the message to 
a neighbor that is generally in the direc- 
tion of the destination. 

Conceptually messages may be of 
arbitrary length. In fact, each message 
is broken up and sent as a sequence 
of fixed-length packets. 



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Inquiry 241 



ARCHITECTURES 



ing list is formed. In terms of the 
definition given above, steps 3 and 4 
would be replaced with null opera- 
tions—variables are just treated as 
"always match" objects. Mock unifica- 
tion is the most powerful subset of 
unification that is state-free. Therefore, 
mock unification is a suitable can- 
didate for integration into VLSI mem- 
ory. Associative-memory systems that 
utilize mock unification as their match 
function are called CxAMs: context- 
addressable memories. 

From a hardware point of view, de- 
signing associative-memory architec- 
tures involves a resource trade-off 
between processing and memory: 
The more hardware devoted to 
"matching," the more data that can be 
examined in parallel, leading to faster 



BITS EQed /( nanosecond *mm2) 
4 



CxAM-3: HCP 15K BITS/mm2 




CxAM-2 



12 3 4 15 

K BITS/mm2 



Figure I : A graph of the range of hit 
and search-power densities for a QAM 
design. 



search time per bit of storage. But 
conversely, the more matching hard- 
ware there is, the smaller the amount 
of hardware that can be devoted to 
data memory and the lower the den- 
sity of the associative memory. The 
data-path bandwidth of the match 
hardware is also a factor in making 
these trade-offs. Therefore, associa- 
tive memories can be rated by their 
storage density (bits stored per unit 
of silicon area) and search throughput 
(bits searched per unit of time per unit 
of silicon area). 

I examined two classes of associa- 
tive memory in which the match func- 
tion is mock unification. One inte- 
grated the matching circuitry with 
memory circuitry, the other was hash- 
based. Hashing was considered 



MINIMUM SYSTEM CONFIGURATION (BITS) 


100M 
10M 

1M 








HASH BASED CxAM 


100K 






10K 




SEARCH BASED CxAM 


IK 


r 








4 8 12 16 




K BITS/mm2 



Figure 2: The minimum-usable-size 
system for use with the hashing QAM. 
Note that the minimum is too large for 
some applications. 



T^ble 2: A list of AUanguage match operations and data types arranged in 
order of complexity. 

Match Hierarchy 


Match Operation 


Object Type 


Compare Instructions 


32-bit data object 


LISP EQ Function 


Atomic LISP objects 


LISP EQUAL Function 


S-Expressions 


Mock Unification 


S-Expression with don't cares 


Unification 


S-Expression with matching variables 


Unification & Predicates 


S-Expression with variables/predicates 


Arbitrary User Code 


arbitrary user representation objects 



because in many applications in the 
past software hashing has dominated 
CAM technology (reference 7). In 
more detail the two classes are 

1. Brute-force search: The contents of 
a memory are exhaustively searched 
by some number of parallel match 
units. For this class of search a custom 
VLSI mock-unification-memory archi- 
tecture was designed. 

2. Hashing: Objects to be fetched are 
hashed, and then the collision list is 
serially searched by a match unit. A 
proposed VLSI implementation of 
PEARLs hashing scheme (called the 
HCP, or hash coprocessor) served as 
an embodiment of hash-based 
searching. In this system the bit 
storage is conventional DRAM. 

Figures 1 and 2 present graphs of 
CxAM design-space trade-offs. Figure 
1 displays the range of bit and search- 
power densities. The hash-based 
CxAM has a single operating point 
because the fetch time is essentially 
independent of memory size as is the 
density. The search-based CxAM has 
a variable range because one can vary 
the relative proportions of storage 
and processing in such architectures. 
The two lines represent two different 
search-based architectures. One has 
inherently better bit density but over 
most of the design space this advan- 
tage is negated by an inherently 
worse search throughput. However, 
neither design completely dominates 
the other— a choice between the two 
will depend on the relative storage- 
density/match-throughput balance 
desired. Figure 2 displays the defect 
of the hashing CxAM. The minimum- 
usable-size system is too large for 
some applications. 

Thus the trade-offs between these 
two schemes turn out to be in den- 
sity and minimum usable size. As a 
representative data point, both tech- 
niques could perform a mock unifica- 
tion of their entire local memory con- 
tents for an average query (an S- 
expression of length 16) in 5 micro- 
seconds. The density of the search- 
based CxAM was about eight times 
worse than that of conventional 
single-transistor DRAM. The hashing 



204 BYTE • APRIL 1985 



Inquiry 25 



Little Board™ $349' 



ARCHITECTURES 



scheme used conventional DRAMs 
and so had high density. But the 
minimum configuration of a hash- 
based CxAM memory system using 
standard 256K-byte DRAMs is 10 
megabits, whereas the search-based 
CxAM can be configured for much 
smaller system storage sizes. 

This extremely high speed of 5 
microseconds portends greatly in- 
creased efficiency for systems bottle- 
necked by database fetch time. But 
which technique to use is very depen- 
dent upon grain size. If you are con- 
structing a large nonparallel machine, 
a bank of HCPs and conventional 
DRAMs works well. But for an array 
of small-grain processors with on-chip 
memories, the search-based CxAM 
approach is more tractable. 

Combining a CxAM with software- 
based routines provides a range of 
tailored matching services with sliding 
power/price/throughput trade-offs. 
The FAIM-1 machine provides an ex- 
ample of this design. For each of 
thousands of processors, there is 
parallel CxAM hardware for mock uni- 
fication, a single, hard-wired, serial 
pipelined full unifier, and software 
support for post-unification matching 
features (attached predicates and 
demons), With such a hardware/soft- 
ware hierarchy, simple matches (like 
LISP's equal) run fast, whereas more 
complex matching services (such as 
KRLs— see reference 1) cost more in 
time due to the software component. 

In summary, matching is a common 
operation ripe for VLSI implementa- 
tion, but the complexity of match 
functions varies. T&ble 2 arranges a 
simple list of match operations and 
data types in order of complexity. 
Successful high-performance AI ma- 
chines will have to carefully decom- 
pose these functions into hardware 
and software components. 

Parallei^Processor 
Communications 

As already mentioned, processors 
working in parallel cannot communi- 
cate objects and messages by sharing 
a large common memory. Some sort 
of special message-passing (and for- 
warding) hardware is essential for ef- 



ficient handling of the traffic. In many 
general-purpose parallel processors, 
interprocessor communication is the 
computational bottleneck. 

Signal-to-Symbol 
Processing 

Despite all the attention given to 
speeding up high-level symbolic com- 
putation, within some AI applications 
the main processing bottleneck has 
been in the very-low-level processing 
of raw sensory data. Within many vi- 
sion systems, 90 percent or more of 
the run time may be incurred in the 
initial segmentation of the visual 
scene from pixels to low-level sym- 
bolic constructs (reference 16). More- 
over, limitations of the higher-level vi- 
sion processing can usually be traced 
to an inadequate initial segmentation 
(reference 4). Similar problems arise 
in many speech systems. In such 
cases, you should look to special- 
purpose VLSI processors to directly 
attack the problem. Examples include 
special image-processing chips (refer- 
ence 14), and speech chips (reference 
2). As array processors have shown, 
for these special processors to be 
usable by programmers they need to 
be very well integrated with the other 
hardware and software components 
of the system and as transparent as 
possible. Since most AI programmers 
are not good microcode hackers, you 
are in trouble if this is the only inter- 
face with a special device. 

Conclusion 

Opportunities for increased efficien- 
cy abound at all levels of AI systems 
if we only look, but to obtain the 
desired throughput increases all the 
potential improvements outlined here 
must be made. We must make hard 
trade-offs between traditional AI pro- 
gramming practices and the discipline 
necessary to construct algorithms that 
can make effective use of large multi- 
processors. We must compile our AI 
languages, and these compilers must 
influence instruction-set design. Key 
computational bottlenecks in AI pro- 
cessing must be attacked with custom 
silicon. There is a real need to use 

{continued) 




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APRIL 1985 'BYTE 205 



ARCHITECTURES 



concurrency at all levels where it 
makes sense, but the overhead must 
be analyzed realistically. ■ 

ACKNOWLEDGMENTS 
The author would like to acknowledge the 
contributions of members of the FAIM-1 
project: Ken Olum for his collaboration on 
the instruction-set benchmarks, Ian Robin- 



son and Erik Brunvand for their VLSI 
CxAM designs, and Al Davis for overall ar- 
chitectural discussions. 

REFERENCES 

I. Bo brow, D, and T. Winograd. An Over- 
view of KRLrO, a Knowledge Representa- 
tion Language." Cognitive Science, vol. 1, no. 

1, 1977. 

2. Burleson, W. "A Programmable Bit-Serial 




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Call or write today for more information: 
Systems Strategies Inc 225 West 34th St. New York, NY 10001 . (212) 279-8400. 



<3> 



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An AGS Company 

Experience... the main link in communications software 



Signal Processing Chip." SM Thesis, MIT 
Department of Electrical Engineering and 
Computer Science, 1983. 

3. Deering, ML I. Faletti, and R/Wilensky. 
"PEARL--A Package for Efficient Access 
for Representations in LISP' Proc. 1JCAI-81 , 
Vancouver, B.C., Canada, August 1981, 
pages 930-932. 

4. Deering, M., and C Collins. "Real-Time 
Natural Scene Analysis for a Blind Pros- 
thesis." Proc. IJCAI-81, Vancouver, B.C., 
Canada, August 1981, pages 704-709. 

5. Deering, M., and K. Olum. "Lisp and 
Processor Benchmarks." Unpublished 
FLAIR Technical Report, March 1984. 

6. Fateman, R. "Is a Lisp Machine Different 
from a Fortran Machine?" S1GSAM, vol. 12, 
no. 3, August 1978, pages 8-11. 

7. Feldman, J., and P Rovner. "An Algol 
Based Associative Language." Commun. 
ACM, vol. 12, no. 8, August 1969. 

8. Foderaro, J. "The Franz Lisp System." 
Unpublished memo in Berkeley 42 UNIX 
Distribution, September 1983. 

9. Gabriel, R., and J. McCarthy. "Queue- 
based Multi-processing Lisp." Preprint, 
1984. 

10. Gajski, D, D Pradua, D. Kuck, and R. 
Kuhn. "A Second Opinion on Data Flow 
Machines and Languages." IEEE Computer, 
vol. 15, no. 2, February 1982, pages 
58-69. 

11. Genesereth, M. "An overview of Meta- 
Level Architecture." Proc. AAA1-83, 
Washington, DC, 1983. 

12. Griss, M., and E. Benson. "Current 
Status of a Portable Lisp Compiler" 
SIGPLAN, vol. 17, no. 6, in Proc. SIGPLAN 
'82 Symposium on Compiler Construction, 
Boston, MA, June 1982, pages 276-283. 

13. Knight, T, Jr., D. Moon, J. Holloway, and 
G. Steele, Jr. "CADR." MIT AI Memo 528, 
March 1981. 

14. Kurokawa, H., K. Matsumoto, M. 
Iwashita, and T. Nukiyama. "The Architec- 
ture and Performance of Image Pipeline 
Processor." Proc. VLSI '83, Troncjheim, Nor- 
way August 1983, pages 275,-284. 

1 5. Lampson, B., and K. Pier. "A Processor 
for a High-Performance Personal Com- 
puter." Proc. Itk Symposium on Computer Ar- 
chitecture, SIGArch/lEEE, La Baule, May 
1980. pages 146-160. 

16. Perkins, W. "A Model Based Vision Sys- 
tem for Industrial Parts." IEEE Trans. Corn- 
put., vol. C-27, 1978, pages 126-143. 

17. Warren, D H. "Applied Logic— Its Uses 
and Implementation as a Programming 
Tool." Ph.D. Dissertation, University of 
Edinburgh, 1977. Available as Technical 
Note 290, Artificial Intelligence Center, SRI 
International. 



206 B YTE • APRIL 1985 



Inquiry 378 



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© Eastman Kodak Company, 1985 



Inquiry 134 



APRIL 1985 • BYTE 207 



'Despite the recent press notices, 
multiuser microcomputers aren't 

anything new!" 



This is the first in a series of 
discussions with Rod Coleman, 
President of Stride Micro 
(formerly Sage Computer) on 
the 68000 multiuser market 
and its current environment. 

Q: Why do you say that? 
RC: "The technology to build a 
high performance multiuser sys- 
tem has been around for five 
years. And while some of the 
leaders in this industry have been 
pretending that micro multiuser 
didn't exist, we've been shipping 
complete systems for nearly three 
years. The benefits of multiuser 
are undeniable; it is more cost ef- 
fective, and offers greater flexibil- 
ity and utility. But until just re- 
cently, the marketing pressure to 
be compatible instead of being 
better, has blinded the industry." 

Q: What do you mean? 
RC: "Well, for example, the 
Motorola 68000 processor intro- 
duced 16/32- bit technology to the 
personal computer world a long 
time ago. It was fully capable of 




A surprising feature is 
compatibility. Everybody 
talks about it, but nobody 
does anything about it" 



meeting high performance and 
multiuser design requirements in 
1980. Instead of this trend taking 
off, most energy was spent pro- 
moting 8088/8086 products that 



were clearly inferior from a tech- 
nical point of view. This phenom- 
enon leads me to believe that they 
will soon rewrite the old proverb: 
'Build a better mousetrap and the 
world will beat a path to your 
door,' but only if they can find the 
way through the marketing fog." 
Q: Are things changing now? 
RC: "Yes and no. With the busi- 
ness world starting to take more 
and more interest in microcompu- 
ter solutions, the advantages of a 
solid multiuser system couldn't be 
kept hidden forever; companies 
like ours and a few others were 
beginning to make a dent. Instead 
of taking a fresh approach, some 
of the newest multiuser offerings 
will probably only give the tech- 
nology an undeserved black eye! 
Multiuser is far more than the 
ability to plug in more terminals. 
It involves things like machine 
compatibility, fast processors, 
adequate memory, large storage 
capacities, backup features, net- 
working, and operating system 
flexibility." 

Q: Is this what makes the new 
Stride 400 Series different? 
RC: "Exactly. That sounds self- 
serving, but it's true. Today a 
number of companies are intro- 
ducing their first multiuser sys- 
tem. We've been building and 
shipping multiuser machines for 
almost three years. We know the 
pitfalls, we've fallen into some of 
them. But we have learned from 
our mistakes." 
Q: Give me some examples. 
RC: A hard disk is almost manda- 
tory for any large multiuser in- 
stallation. Yet, backing up a hard 
disk can be a nightmare if you 
only have floppies to work with. 
That's why we've added a tape 
backup option to all the larger 
Stride 400 Series machines. It's 
irresponsible for a manufacturer 
to market a multiuser system 
without such backup. Another 
good lesson was bus design. We 
started with one of our own de- 
signs, but learned that it's impor- 
tant not only to find a bus that is 
powerful, but also one that has 
good support and a strong future 
to serve tomorrow's needs. We 




"The marketing pressure 

to be compatible 

instead of being better, 

has blinded the industry." 



think the VMEbus is the only de- 
sign that meets both criteria and 
thus have made it a standard fea- 
ture of every Stride 400 Series 
machine." 

Q: What are some of the other 
unique features of the 400 Series? 
RC: "A surprising feature is com- 
patibility. Everybody talks about 
it, but nobody does anything 
about it. Our systems are com- 
pletely compatible with each other 
from the 420 model starting at " 
$2900, through the 440, on to the 
powerful 460 which tops out near 
$60,000. Each system can talk to 
the others via the standard built-in 
local area network. Go ahead and 
compare this with others in the in- 
dustry. You'll find their little ma- 
chines don't talk to their big ones, 
or that the networking and multi- 
user are incompatible, or that they 
have different processors or 
operating systems, and so on." 
Q: When you were still known as 
Sage Computer, you had a reputa- 
tion for performance, is that still 
the case with the new Stride 400 
Series? 

RC: "Certainly, that's our calling 
card: Performance By Design.* 
Our new systems are actually fas- 
ter; our standard processor is a 10 
MHz 68000 running with no wait 



states. That gives us a 25% in- 
crease over the Sage models. 
And, we have a 12 MHz pro- 
cessor as an option. Let me add 
that speed isn't the only way to 
judge performance. I think it is 
also measured in our flexibility. 
We support a dozen different 
operating systems, not just one. 
And our systems service a wide 
variety of applications from the 
garage software developer to the 
corporate consumer running high 
volume business applications." 
Q: Isn't that the same thing all 
manufacturers say in their ads? 
RC: "Sure it is. But to use another 
over used- term, 'shop around'. 
We like to think of our systems as 
'full service 68000 supermicro- 
computers.' Take a look at every- 
one else's literature and then 
compare. When you examine 
cost, performance, flexibility, and 
utility, we don't think there's any- 
one else in the 
race. Maybe 
that's why we've 
shipped and 
installed more 
multiuser 68000 
systems than 
anyone else." 




Formerly Sage Computer 

For more information on Stride or 
the location of the nearest Stride 
Dealer call or write us today. 
We'll also send you a free copy of 
our 32 page product catalog. 

Corporate Offices: 
4905 Energy Way 
Reno, NV 89502 
(702)322-6868 

Regional Offices: 
Boston: (617) 229-6868 
Dallas: (214) 392-7070 



208 BYTE • APRIL 1985 



Inquiry 367 



ARTIFICIAL INTELLIGENCE 



THE LISP 
REVOLUTION 



A LITTLE MORE than five years ago, 
a friend from a major computer cor- 
poration came into my office to talk 
about developing artificial-intelligence 
(AI) packages. "How should we get 
started?" he asked. My answer was 
gloomy: 

First, get together a million 
dollars or so and buy one of 
Digital Equipment Corporation's 
(DEC'S) big mainframe com- 
puters. Next, decide what 
dialect of LISP to run, choosing 
from MacLISP. InterLISR Por- 
table Standard LISP, Franz LISP, 
and many others. Then try to 
get a tape from somewhere and 
find someone who can install it. 
You'll probably find that the 
documentation is not particular- 
ly complete and software main- 
tenance will be a problem. And 
if you bet on the wrong dialect 
now, changing to another will 
certainly take a lot of work. 

Tbday, by contrast, I wrote this arti- 
cle using an editor written in LISP. The 
editor is part of a $500 LISP system 
that I use on a $4000 personal com- 
puter. I wrote and tested a program 
in the $500 LISP that I will be able to 



by Patrick H. Winston 

LISP is no longer 
limited to a lucky few 



run without change on a supersophis- 
ticated, superpowerful Symbolics 
3670. TWo things have made this prog- 
ress possible. First, the recent avail- 
ability of personal computers with 
512K bytes of memory, which is 
enough to learn LISP and to start ex- 
periencing the excitement of its appli- 
cations in AI. Second, Common LISP 
emerged as the heir apparent to all 
previous LISP dialects. The same 
Common LISP program you write on 
a personal computer can be trans- 
ferred later to a heftier machine, as 
needs and resources permit. 

Data General, DEC, Hewlett- 
Packard, LISP Machine, Symbolics 
Inc., Tfexas Instruments, and Xerox all 
sell versions of Common LISP for 
their own machines, and Common 
LISP is available for personal com- 
puters as well. Suddenly, serious LISP 
programming is no longer limited to 
a lucky few. 

LISP Means Symbol 
Manipulation 

The reason that LISP is different from 
most other languages is that LISP 
focuses on symbol manipulation 
rather than on numbers. To highlight 
the difference, I'll lay out some ex- 



amples of symbol manipulation taken 
from the Mover program, one that 
moves toy blocks like those shown in 
figure 1. Specialized problem-solving 
procedures inside the Mover program 
enable it to get rid of obstacles that 
are in the way. These problem-solving 
procedures use and maintain informa- 
tion about what each object supports. 
For example, B3 supports B1 and B4. 
The Mover program knows this 
because the symbols B1 and B4 are 
found in a list obtained from B3 by 
the get instruction: 

(get 'B3 things-supported) 
-> (B1 B4) 

Now suppose we have attached the 
list of things that B3 supports to a 
variable called obstacles. LISP's 
symbol-manipulation primitives allow 
for quick answers to basic questions: 

How many obstacles are there? 
(length obstacles) — > 2 

{continued) 

Patrick Henry Winston (MIT Artificial In- 
telligence laboratory, 545 Technology Square, 
Cambridge, MA 02139) has a B.S., M.S., 
and Ph.D. from MIT. He does research on 
computer learning and directs the Artificial 
Intelligence laboratory at MIT 



APRIL 1985 -BYTE 209 



LISP REVOLUTION 



What's the first obstacle? 

(first obstacles) — > B1 

Is Bl an obstacle? 

(member B1 obstacles) — > t 

Is B4 the first obstacle? 

(eq B4 (first obstacles)) — > nil 

Note that t is LISP notation for true, 
and nil is LISP notation for false. Other 
symbol-manipulation primitives 
facilitate changes to the list and test 
to see if it is empty: 

Remove B4 from the list: 
(sett obstacles 

(remove B4 obstacles)) — > (B1) 
Add B7 to the list: 
(setf obstacles 

(cons B7 obstacles)) — > (B7 B1) 
Is the obstacle list empty? 
(endp obstacles) — NIL 

Once changed, the obstacle list can 
be reattached to the symbol B3 from 



which it came: 

(setf (get B3 things-supported) 
obstacles) 

All these questions and changes are 
simple, low-level examples of the sym- 
bol manipulation for which LISP is 
famous. Similar symbol-manipulation 
feats enable the Mover program to 
keep track of what is done. Mover's 
history-maintaining procedures con- 
tain instructions that examine and 
change symbolic expressions describ- 
ing every move. Those symbolic de- 
scriptions make it possible to answer 
questions like: Did you move block 
B7? How did you move block B7? 
Why did you move block B7? When 
did you move block B7? 

Thus symbol manipulation enables 
Mover to exhibit a humanlike intro- 
spective ability to explain itself. Sym- 
bol manipulation is so intimately as- 



Listing I : A procedure found inside the Mover program illustrating the problem- 
reduction heuristic. 



(defun put-at (object place) 
(grasp object) 
(move-object) 
(ungrasp object)) 



; Define the PUT-AT procedure. 

; Grasp the object— may require moving obstacles. 

;Move the object— easy. 

;Move the object— easy, too. 



- TRAY. THE BLOCKS WORLD 



SLIDE 9 OF 10- 

11 



Bl 



H 



B3 



B5 


l-l 
l-.l 


B8 


B6 



THE OBJECTIVE HERE IS TO PUT BLOCK B6 ON TOP OF BLOCK B3. CALLED FOR 
BY THE FOLLOWING INSTRUCTION: 

tPROGN (PUT-ON ' B6 ' B3) ' DONE). 

SPACE-NEXT SLIDE 



Figure 1 : A picture of the blocks world in which the Mover program operates. 



sociated with AI, it's no wonder that 
LISP is the key language used in AI 
applications. 

Computer Professionals 
Should Know LISP 

LISP experts argue endlessly about 
why LISP remains the primary lan- 
guage for AI and about why it is 
becoming a language for general- 
purpose programming as well. Some 
say LISP's primitives and features ex- 
plain all. Others claim LISP owes its 
power to its tradition of interactive 
programming and powerful debug- 
ging tools. Still others cite its simple 
hierarchy-encouraging procedure- 
definition mechanism. {Editor's note: for 
a short introduction to LISP, see "LISP for 
the IBM Personal Computer" by \ordan Bortz 
and John Diamant, }uly 1984 BYTE, page 
281.| 

Increasingly, LISP is becoming a 
more generally used language, not 
strictly limited to applications in AI. 
Because many of the systems of AI 
are large, LISP has become a lan- 
guage suited to large-system imple- 
mentation. For example, it has been 
used with outstanding success in 
building the entire operating systems 
of the LISP machines now offered by 
a growing number of major com- 
panies. 

Such successes are one reason why 
many computer-science educators 
believe that an understanding of LISP 
is de rigueur for computer science 
majors. Another is that LISP has been 
proven an excellent language for il- 
lustrating computing concepts. At 
MIT, for example, a dialect of LISP 
called Scheme has been used for 
years as the primary language in the 
basic introductory subject on pro- 
gramming languages. 

LISP Is Both Old and New 

Before you learn any computer lan- 
guage, you should ask if the language 
is too old to be modern or too new 
to be mature. What about LISP? Is it 
too old or too new? Many people are 
surprised to learn that the history of 
LISP goes back to the late 1950s, 
making LISP nearly as old as FOR- 

{continued) 



210 BYTE • APRIL 1985 



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LISP REVOLUTION 



TRAN. Unlike FORTRAN, however, the 
LISP of today is much different from 
the LISP of 2 5 or even 5 years ago. 
Why did FORTRAN calcify while LISP 
continued to evolve vigorously? The 
principal reason is that FORTRAN was 
suited to commercial applications ear- 
ly on, whereas LISP was not. LISP re- 



quires a lot of memory and in the 
days when memory was expensive, 
there was no commercial purpose 
served by early standardization of 
LISP Consequently, LISP dialects pro- 
liferated, LISP innovations thrived, 
and cross-fertilizations from one 
dialect of LISP to another kept each 



MAKE -SPACE FIND- SPACE 




^GET-RID-OF- 
PUT-AT I CLEAR -TOP 




MOVE-HAND 







PLACE 


X 


Y 


/ 




START 


GOAL 


START 





2 


\ 


/ \ 


A 


2 





A 


-B C 


B 


5 









c 


10 









D 


2 


4 






E 


7 


4 






GOAL 


7 


2 



Figure 2: Graphical description of how 
all the procedures in Mover work together. 



Figure 3: An example of a maplike net. 



(make-rule identifyl 6 






if 


((> 


animal) is 


a(> type)) 






((< 


animal) is 


a parent of (> 


child)) 


then 


((< 


child) is a 


(< type))) 





Figure 4: A rule ready for inclusion in a USP-based animal-recognition system. 



Rule IDENTIFY1 asserts (ROBBIE IS A MAMMAL) 


because 


(ROBBIE HAS HAIR) 


Rule IDENTIFY5 asserts (ROBBIE IS A CARNIVORE) 


because 


(ROBBIE EATS MEAT) 


Rule IDENTIFY9 asserts (ROBBIE IS A CHEETAH) 


because 


(ROBBIE HAS DARK SPOTS) 




(ROBBIE HAS TAWNY COLOR) 




(ROBBIE IS A CARNIVORE) 




(ROBBIE IS A MAMMAL) 


Rule IDENTIFY16 asserts (BOZO IS A MAMMAL) 


because 


(ROBBIE IS A PARENT OF BOZO) 




(ROBBIE IS A MAMMAL) 


Rule IDENTIFY16 - R' - F 


because 


(ROBBIE IS A PARENT OF BOZO) 




(ROBBIE IS A CARNIVORE) 


Rule IDENTIFY16 asserts (BOZO IS A CHEETAH) 


because 


(ROBBIE IS A PARENT OF BOZO) 




(ROBBIE IS A CHEETAH) 



Figure 5: Output fragment showing how a forward-chaining rule moves from facts to 

conclusion. 



about as powerful as any other. Now, 
however, memory is relatively cheap, 
which is attracting many commercial 
users to LISP, thus increasing the need 
for a standardized LISP for applica- 
tions and instruction. Fortunately, the 
2 5 years LISP has had to mature 
means that many new features have 
been incorporated into the Common 
LISP standard. Here are some of my 
favorites: 

• a powerful structure-defining 
primitive that automatically generates 
procedures for accessing record fields 

• a generalized assignment primitive 
that works for values, properties, ar- 
rays, and structures 

• a flexible template-filling mechan- 
ism that enables complicated expres- 
sions to be constructed easily and 
transparently 

• a strong macrocomputer capability 
that enables users to dream up their 
own syntax 

• a rich variety of argument-passing 
options, including optional arguments 
with specifiable defaults as well as 
arguments associated with param- 
eters by way of key words 

• a modern, stream-oriented input/ 
output (I/O) system 

How to Learn LISP 

I think the best way to learn LISP is 
interactively. There are quite a 
number of reasons why such inter- 
active learning is good. For instance: 
It's fun to do on-line puzzles; it's bor- 
ing to do exercises in a book. It's 
easy to demystify difficult points by 
trying things out immediately. It's 
motivating to watch interesting pro- 
grams work. 

In any case, one factor stands undis- 
puted: LISP programming is fun. Let's 
look at a few taken from an on-line, 
interactive instruction package known 
as the San Marco LISP Explorer. 
{Author's note: The San Marco LISP Ex- 
plorer package is sold by Gold Hill Computers 
Inc., 163 Harvard St., Cambridge, MA 
02139.| We will examine the Mover 
blocks-manipulation program, the 
search program, the rule-based ex- 

{continued) 



212 B YTE • APRIL 1985 



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APRIL !985 'BYTE 213 



LISP REVOLUTION 



Listing 2: A search program that finds paths through maplike nets such as the 
one in figure 3. 



(defun start-depth (start goal)) 
(depth (list (list start)) 
goal)) 



;Make a one-partial-path queue. 
;Pass along name of goal place. 



(defun depth (queue goal) 
;;lf no other partial paths, quit: 
(if (null queue) 
nil 

;;Otherwise, if goal found, quit: 
(if (equal goal (first (last (first queue)))) 
(first queue) 

;;Otherwise, expand first partial path 
;;and add to FRONT of queue: 
(depth (append (expand (first queue)) 
(rest queue)) 
goal))))) 

(defun expand (path) 
(let ((reversed- path (reverse path))) 
;;Turn the new partial paths right way around: 
(mapcar 'reverse 
;;Get rid of partial paths that close on themselves: 
(remove-if '(lambda (new- path) 

(member (first new- path) (rest new- path))) 
;;Make one new partial path for each neighbor: 
(mapcar '(lambda (neighbor) (cons neighbor reversed-path)) 
;;Get neighbors: 
(get (first reversed-path) 'neighbors)))))) 



Listing 3: The expression-matching procedure in any rule-based expert system 
must compare expressions and produce a list of pattern-match pairs. 



* (match '((> animal) is a (> type)) 
'(Robbie is a Cheetah) 
nil) 

((animal robbie) (type cheetah)) 



; First argument is a pattern. 

;Second argument is an assertion. 
Third is a list of prior pattern-match 
; pairs, none in this example. 
The answer— a list of pattern- matches. 



Listing 4: A matcher program for a rule-based expert system. 


(defun match (p d matches) 






(cond ((and (endp p) (endp d)) 




Succeed. 


(cond ((endp matches) t) 






(t matches))) 






((or (endp p) (endp d)) nil) 




Fail. 


((equal (first p) (first d)) 




Identical first elements. 


(match (rest p) (rest d) matches)) 




Match the rest. 


((atom (first p)) nil) 




Losing atom. 


((equal (first (first p)) ' >) 




Match > variable. 


(match (rest p) (rest d) 






(shove-value (second (first 


P)) 




(first d) 






matches))) 






((equal (first (first p)) '<) 




Substitute variable. 

[continued) 



pert system, and the natural-language 
interface. 

Planning 

in the Blocks World 

LISP programs are generally ex- 
amples of the problem-reduction 
heuristic; that is, to solve a hard prob- 
lem you must break it up into simpler 
subproblems. The problem-reduction 
heuristic can be seen in the simple 
Mover program. Listing 1 is a pro- 
cedure found inside the Mover pro- 
gram that breaks the problem of put- 
ting an object somewhere into three 
subproblems: grasp it, move it, and 
ungrasp it. Figure 2 is a graphical 
description of how all of the pro- 
cedures in Mover work together. LISP 
encourages the creation of layered 
programs, like Mover, wherein big 
problems are broken down succes- 
sively into smaller and smaller 
problems. 

Searching 

in the Map World 

Search techniques are commonly 
used in AI to solve problems. Here 
are some examples: 

• finding a route through a highway 
net 

• finding a way to put together a 
motor 

• understanding a written database 
request 

• learning to recognize a plant 
disease 

Abstractly, search problems all 
amount to finding a way through 
some sort of maplike net. Figure 3 is 
a sample of such a net. The goal is 
close to place E, but there is no direct 
connection; E is a dead end. There 
are two ways to go from B to the goal: 
directly, and indirectly, through C. 
Listing 2 shows a page of LISP defin- 
ing a search program that finds paths 
through these maplike nets. Although 
you won't understand much of the 
program if you don't know LISP yet, 
you may enjoy looking at its overall 
structure and simplicity With a little 
more effort, you can define a search 

[continued) 



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LISP REVOLUTION 



(match (cons (pull-value (second (first p) matches) 
(rest p)) 
d 
matches))))) 

This matcher happens to use two auxiliary procedures: 

(defun pull-value (variable a-list) 
(second (assoc variable a-list))) 

(defun shove- value (variable item a-list) 
(append a-list (list (list variable item)))) 



Listing 5: A program that matches sentences against a suitable representation 
of semantic grammars and activates the appropriate search procedure. 

(record question 

((branch ((parse present) 

(branch (THE (parse attributes) OF (parse tools) 
(parse-result-if-end 
(report- attributes attributes tools))) 
((parse tools) S (parse attributes) 
(parse-result-if-end 
(report-attributes attributes tools))))) 
(HOW MANY METERS IS (parse tooll) FROM (parse tool2) 
(parse-result-if-end 
(report-distance tooll tool2))) 
(IDENTIFY (parse tools) 

(parse-result-if-end 

(report-identity tools))) 
(COUNT (parse tools) 

(parse-result-if-end 

(report-number tools)))))) 



i present 



OF 



i tools 



->0 



THE 1 attributes 

>0 >0-- - >0- 

I tool S 4 attributes 

>o >o >0 

HOW MANY METERS IS 1 tooll FROM 1 tool2 

• >0 >0 >0 >0 

IDENTIFY i tools 

>0 > 

COUNT i tools 

->0 - >0 



Figure 6: The top level of a semantic grammar capable of handling queries about the 
color, weight, length, and position of some tools. 




What are the weight, length, and color of the saw? 



i present THE i attributes 



OF i tools 



Figure 7: An example of a question that matches the top level of the semantic 
grammar in figure 6. 



procedure that finds the guararv 
teed-shortest path. 

Analysis 

in the Zoo World 

Rule-based expert systems are the 
hottest thing in the commercialization 
of AI. All of them are built on the idea 
that some kinds of knowledge can be 
reduced to simple rules. Figure 4 
shows one rule that is ready for inclu- 
sion in a LISP-based animal-recogni- 
tion system, which expresses the fact 
that an animal's children are animals 
of the same kind. LISP does not have 
any built-in primitives that handle 
such rules, but it is a splendid 
language in which to embed a rule- 
exploiting program. LISP'S symbol- 
manipulating power is well suited to 
the task of examining the symbols 
that make up a rule, comparing them 
to the symbols that make up the ex- 
isting facts, and reacting accordingly. 
One kind of rule-exploiting program 
is a forward-chaining rule interpreter, 
which is a program that uses rules to 
move forward from facts to conclu- 
sions. Figure 5 is an output fragment 
showing what such a program does 
with facts about Robbie, knowledge 
about the relationship between Rob- 
bie and Bozo, and a few rules. There 
is always an expression-matching pro- 
cedure buried inside any rule-based 
expert system like the animal- 
identification procedure. While the 
entire system is too lengthy to show, 
the matcher is short and straightfor- 
ward. Its task is to compare expres- 
sions and to produce a list of pattern- 
match pairs, as shown in listing 3. 
Listing 4 is the matcher program. 

Interaction 

in the Tool World 

The pattern matcher shown previous- 
ly is not just an important part of a 
rule-based system. It is also just about 
all you need to make the famous Doc- 
tor program, the one that pretends it 
is a psychiatrist responding with ap- 
parent sympathy as you pour your 
heart out over family traumas. More 
importantly, the pattern matcher has 
a family resemblance to natural-lan- 

{continued) 



216 BYTE • APRIL 1985 




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APRIL 1985 -BYTE 217 



LISP REVOLUTION 



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screwdriver from the big blue one? 
The top level of a semantic gram- 
mar capable of handling all these 
queries is shown in figure 6. A 
semantic-grammar interpreter finds 
paths through such a net using input 
sentences as a guide. Each branch 
marked with a > symbol requires 
traversal of a subnet. Each complete 
path from the entry to an exit is 
associated with its own data-search- 
ing procedure. For example the 
sentence in figure 7 matches the top- 
most path in the top-level net. Three 
subnets are traversed in addition to 
the top-level net. Once again, LISP'S 
symbol-manipulating power makes it 
easy to write a program that both 
matches sentences against a suitable 
representation of semantic grammars 
and activates the appropriate search 
procedures. Listing 5 shows what such 
a representation looks like when it 
is rendered in LISP-oriented nota- 
tion. 

Conclusion 

We really don't need any new ex- 
amples to demonstrate why profes- 
sionals need to know about LISP. The 
examples presented are all elemen- 
tary but they indicate the sorts of 
things done by their bigger brothers. 
LISP is the foundation for expert 
systems of all kinds, many of which 
have progressed far beyond the sim- 
ple rule-based paradigm. LISP is the 
language for most natural-language 
development efforts. Indeed, LISP is 
the language of choice for most peo- 
ple working in AI— supporting work 
that includes learning, instruction, 
speech, vision, robotics, and all sorts 
of reasoning. ■ 

BIBLIOGRAPHY 

Abelson, Harold, and Gerald Jay Sussman. 
Structure and Interpretation of Computer Pro- 
grams. Cambridge, MA: MIT Press. 1984. 
Winston, Patrick H. Artificial Intelligence, 2nd 
ed. Reading, MA: Add i son-Wesley 1984. 
Winston, Patrick H.. and Berthold K. P. 
Horn. LISP. 2nd ed. Reading, MA: 
Addison-Wesley 1984. 
Winston, Patrick H.. and Karen A. 
Prendergast. The A I Business: The Commer- 
cial Uses of Artificial Intelligence. Cambridge, 
MA: MIT Press, 1984. 

— Inquiry 239 



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APRIL 1985 -BYTE 219 




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Z-8— User defined registers 
names, standard Zilog and Z-80 
style support. Tec Hex output option. 
8748— standard Intel and Z-80 
style syntax supported. 
8051 —51 2 User defined register 
or addressable bit names. 
6800 Family — absolute or 
relocatable modes, all addressing 
modes supported. Motorola syntax 
compatible. Intel Hex or S-Record 
format output. 

6502— Standard syntax or Z-80 
type syntax supported, all 
addressing modes supported. 



220 BYTE • APRIL 1985 



















ZILOG 


• 


OLIVETTI 




Z80 


SYSTEM 8000 


IBM PC 


IBM PC 


M-20 




CP/M" 


UNIX 


MSDOS 


CP/M 86 


PCOS 


Z8000™ 


$299.50 








$299.50 


Z80 


99.50 


500.00 


199.50 


199.50 


199.50 


Z8 


199.50 


500.00 


199.50 


199.50 


199.50 


8086/88 


199.50 


750.00 


99.50 


99.50 


199.50 


80186 


199.50 


750.00 


199.50 


199.50 


199.50 


8748 


199.50 


500.00 


199.50 


199.50 


199.50 


8044/51 


199.50 


500.00 


199.50 


199.50 


199.50 


8080 


199.50 


500.00 


199.50 


199.50 


199.50 


8085 


199.50 


500.00 


199.50 


199.50 


199.50 


8096 


199.50 


500.00 


199.50 


199.50 


199.50 


68020 


399.50 


750.00 


399.50 


399.50 


399.50 


68000,08,10 


299.50 


750.00 


299.50 


299.50 


299.50 


6800,02,08 


199.50 


500.00 


199.50 


199.50 


199.50 


6801 ,03 


199.50 


500.00 


199.50 


199.50 


199.50 


6804 


199.50 


500.00 


199.50 


199.50 


199.50 


6805 


199.50 


500.00 


199.50 


199.50 


199.50 


6809 


199.50 


500.00 


199.50 


199.50 


199.50 


32000 


399.50 


750.00 


399.50 


399.50 


399.50 


COPS400 


199.50 


500.00 


199.50 


199.50 


199.50 


NSC800 


199.50 


500.00 


199.50 


199.50 


199.50 


6301 


199.50 


500.00 


199.50 


199.50 


199.50 


6501/11 


199.50 


500.00 


199.50 


199.50 


199.50 


6502 


199.50 


500.00 


199.50 


199.50 


199.50 


65C02 


199.50 


500.00 


199.50 


199.50 


199.50 


1802 


199.50 


500.00 


199.50 


199.50 


199.50 


F8/3870 


199.50 


500.00 


199.50 


199.50 


199.50 


NEC7500 


199.50 


500.00 


199.50 


199.50 


199.50 


NCR/32 


399.50 


750.00 


399.50 


399.50 


399.50 


Subtotal 


$ 


$ 


$ 


$ $ 




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APRII 


- 1985 -BYTE 221 



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Inquiry 4 



ARTIFICIAL INTELLIGENCE 



THE CHALLENGE 
OF OPEN 
SYSTEMS 



by Carl Hewitt 



Current logic programming methods may be insufficient 
for developing the intelligent systems of the future 



SYSTEMS OF INTERCONNECTED 
and interdependent computers are 
qualitatively different from the 
relatively isolated computers of the 
past. Such 'open systems" uncover 
important limitations in current ap- 
proaches to artificial intelligence (AI). 
They require a new approach that is 
more like organizational design and 
management than current approach- 
es. In this article we'll take a look at 
some of the implications and con- 
straints imposed by open systems. 

Open systems are always subject to 
communications and constraints from 
outside. They are characterized by the 
following properties: 

• Continuous change and evolution. Dis- 
tributed systems are always adding 
new computers, users, and software. 
As a result, systems must be able to 
change as the components and 
demands placed upon them change. 
Moreover, they must be able to evolve 
new internal components in order to 
accommodate the shifting work they 
perform. Without this capability, every 
system must reach the point where it 
can no longer expand to accommo- 



date new users and uses. 

• Arms-length relationships and decentralized 
decision making. In general, the com- 
puters, people, and agencies that 
make up open systems do not have 
direct access to one another's inter- 
nal information. Arm's-length relation- 
ships imply that the architecture must 
accommodate multiple computers at 
different physical sites that do not 
have access to the internal com- 
ponents of others. This leads to de- 
centralized decision making. 

• Perpetual inconsistency among knowledge 
bases. Because of privacy and discre- 
tionary concerns, different knowledge 
bases will contain different perspec- 
tives and conflicting beliefs. Thus, all 
the knowledge bases of a distributed 
AI system taken together will be 
perpetually inconsistent. Decentraliza- 
tion makes it impossible to update all 
knowledge bases simultaneously. This 
implies that it is not even possible to 
know what kinds of information are 
contained in all the local knowledge 
bases in the system at any one time. 
Systems must be able to operate in 
the presence of inconsistent and in- 
complete knowledge bases. 



• Need for negotiation among system com- 
ponents. In a highly distributed system, 
no system component directly con- 
trols the resources of another. The 
various components of the system 
must persuade one another to pro- 
vide capabilities. Consequently a 
distributed AI system's architecture 
must support a mechanism for 
negotiation among components. 

• Inadequacy of the closed-world assumption. 
The closed-world assumption is that 
the information about the world be- 
ing modeled is complete in the sense 
that exactly those relationships that 
hold among objects can be derived 
from the local information possessed 
by the system. Systems that depend 
on the closed-world assumption make 
use of the principle that they can find 

[continued) 

Carl Hewitt received his Ph.D. from the 
Massachusetts Institute of Technology in 1971 
and since then has worked in the field of ar- 
tificial intelligence on foundational issues. His 
outside interests include hiking and skiing. 
Professor Hewitt can be reached at the MIT 
Artificial Intelligence Laboratory, 545 
Technology Square, Room 813, Cambridge, 
MA 02139. 

APRIL 1985 -BYTE 223 



OPEN SYSTEMS 



all existing instances of a concept by 
searching their local storage At first 
glance it might seem that the closed- 
world assumption, almost universal in 
the AI literature, is smart because it 
provides a ready default answer for 
any query. Unfortunately, the default 
answers provided become less 
realistic as open systems increase in 
size and less of the information is 
available locally. 

Continuous growth and evolution, 
arm's-length relationships, incon- 
sistency among knowledge bases, de- 
centralized decision making, and the 
need for negotiation are interdepen- 
dent and necessary properties of 
open systems. 

Parallel Computation 
in Open Systems 

The theory of recursive functions (e.g., 
Hiring machines) is based on a batch- 
processing model of computation. 
Output is obt^ined from a recursive 
function when it finally halts. Open 
systems require a theory of computa- 
tion in which processing might never 
halt, may be required to provide out- 
put while still in operation, and can 
accept input from sources not antici- 
pated when the computation began. 

Asynchronous parallel computer 
systems make use of a two-input, two- 
output computing element called an 
arbiter. Arbiters are the fundamental 
hardware primitives that make parallel 
asynchronous computing different 
from sequential synchronous com- 
puting. Arbiters make decisions for 
which there is no logical justification 
(proof) because the decision cannot 
be predicted from knowledge of the 
structure of the computing system 
and its input. In a very fundamental 
sense arbiters are not equivalent to 
Tliring machines (see reference 3). 
Figure 1 shows an arbiter with inputs 
x and y and outputs x and y\ 

An arbiter decides the order in 
which it receives requests. Thus, if in- 
puts x and y are asserted at about the 
same time, the result will eventually 
be one of the possibilities shown in 
figure 2. 

The output of an arbiter is not a 







» X 1 


ARBITER 













Figure 1: An arbiter, with inputs x and 
y and outputs x and y'. 



ARBITER 



OR 





ARBITER 













Figure 2: Given that the inputs to the 
arbiter are asserted almost simultaneously, 
the resulting output will be one of the 
above two cases. 



S7 „ 




»0 






ARBITER 




.96 - 




* l 





Figure 3: \n practice, the inputs to an 
arbiter are analog signals varying between 
1 and 0. 



logical function of its input, in the 
sense that it is not a simple Boolean 
function, because the dimension of 
time enters into the semantics of ar- 
biter modules in a fundamental way. 
However, the feasible sets of outputs 
can be described in logic using the 
subsequently relation (see reference 1): 

(x=l and y=\) subsequently 
(or 
(x'=0 and y'= 1) 
(x'=l and y'=0)) 

Logic cannot be used to determine 
which particular eventuality will occur. 
Systems with arbiters are not equiva- 
lent to a nondeterministic Tliring 



machine, since an arbiter can require 
an unbounded amount of time to 
make a decision (possibly while other 
computations are taking place). If a 
nondeterministic Tliring machine is re- 
quired to make a decision, there is a 
bound on the amount of time it can 
take, and this bound is determined 
before it starts. Each individual choice 
of a nondeterministic TUring machine 
takes one step. 

In practice, the inputs to an arbiter 
are analog signals that vary con- 
tinuously between and 1. For exam- 
ple, if the actual inputs to an arbiter 
were .97 and .96, then the output 
might be as shown in figure 3. 

The arbiter has only digital outputs 
(0s or Is) even though the input is 
analog. It makes a definite digital 
choice out of the analog quantities of 
time and its two inputs. Because of 
the continuous nature of time and the 
analog nature of the input, an arbiter 
cannot be strictly modeled as a non- 
deterministic-state machine. 

In a parallel computation, arbiters 
are used repeatedly so that the 
number of possibile outcomes grows 
exponentially with time. Thus, the ac- 
tual operation of a parallel computer 
system cannot be determined logical- 
ly by the inputs to the system. The in- 
determinacy of the arbiters used in 
open computer systems results in 
their making decisions that cannot be 
proved from knowledge of structure 
of the computing system and its input. 

Decisions Justified 
by Agreements 

The electronic-banking system is a 
good example of an open system. 
You're probably familiar with it 
through the use of automated teller 
machines that enable you to withdraw 
cash thousands of miles from where 
you opened an account. Teller ma- 
chines are continually being added to 
the system. 

Decisions about which transactions 
to honor are justified on the basis of 
an agreement between the bank and 
its depositors. Often an agreement 
will provide that the bank does not 
have to honor a withdrawal if there 
are insufficient funds present in the 



224 BYTE • APRIL 1985 



OPEN SYSTEMS 



account when the withdrawal is re- 
quested. The withdrawal would be 
refused even though it might be 
covered by subsequent deposits. 

The decisions of which withdrawals 
not to honor cannot be deduced from 
complete information about the struc- 
ture of the bank's computers and the 
input from the teller machines. Thus, 
the decision whether or not to honor 
a withdrawal is not subject to logical 
proof. For example suppose Account 
1 has a balance of $1000, Account 2 
has a balance of $2000, and they 
share a common reserve account with 
a credit limit of $3000. If two elec- 
tronic withdrawals of $4000 each are 
attempted at about the same time 
from both Account 1 and Account 2, 
then one of the attempts will be re- 
fused and the other one will be 
honored, though it is impossible to 
deduce which one will be honored 
and which one refused. 

The above example shows how a 
decision of an open system can be 
justified even though it does not 
follow from any proof. Instead, the 
decision is justified by an agreement 
to act in certain ways. We see a 
divergence between the theories 
used in the construction of open 
systems and their operation. Theory 
informs practice; eg., the design of 
the banking mechanism is based on 
a financial theory. However, the finan- 
cial theory does not determine the ac- 
tual operations of the bank account- 
ing system. The operation of the bank 
accounts is determined by the order 
in which asynchronous events occur 
inside the system. Each performance 
of a complicated open system is 
unique. 

This illustrates the divergence be- 
tween classic recursive-function 
theory and theories needed to model 
open systems. (For a further discus- 
sion of the mathematical semantics 
needed to model the behavior of 
open systems, see references I and 
3.) 

Exploration vs. Search 

Searching in problem spaces is the 
traditional AI framework. Problem 
spaces and problems have been de- 



fined as follows (see reference 16): 

Problem Space: A problem space 
consists of a set of symbolic struc- 
tures (the states of the space) and a 
set of operators over the space. Each 
operator takes a state as input and 
produces a state as output, although 
there may be other inputs and out- 
puts as well. The operators may be 
partial, i.e., not defined for all states. 
Sequences of operators define paths 
that thread their way through se- 
quences of states. 

Problem: A problem in a problem 
space consists of a set of initial 

states, a set of goal states, and a set 
of path constraints. The problem is to 
find a path through the space that 
starts at any initial state, passes only 
along paths that satisfy the path 
constraints, and ends at any goal 
state. 



A good example of a problem 
space is that of the game of chess: 

1. initial state: chess pieces in starting 
position 

2. Operations: legal moves 

3. Goal states: checkmate stalemate, 
etc. 

I claim that searching through prob- 
lem-solving spaces provides a narrow 
foundation for the analysis and syn- 
thesis of intelligent systems. The 
perspective must be broadened to in- 
clude exploration that goes beyond 
search. An excellent perspective on 
some of the differences between 
search and exploration is provided by 
the means used to explore and de- 
velop the North American continent. 

1. Initial state: There was no well- 
defined initial global state of the 

[continued) 



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APRIL 1985 • BYTE 225 



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226 BYTE * APRIL 1985 



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Inquiry 321 



OPEN SYSTEMS 



North American continent in the mid- 
dle 1600s. Leif Ericson and Chris- 
topher Columbus had led some early 
probes, but the information was 
fragmentary, dispersed, and self- 
contradictory. 

2. Operations: The set of operations 
used to explore the continent was not 
defined in advance. Instead, it was im- 
provised dynamically and interactive- 
ly in the course of initial probes. Fur- 
thermore the explorers operated in 
parallel so that there is no path of 
states of the continent that adequate- 
ly explains how it was explored. That 
is, the continent was not explored by 
finding a single path through a space 
of states. Exploration of the North 
American continent can be better 
modeled as a partial order of causal- 
ly linked historical events than as a 
problem space. 

3. Goal states: There was no set of im- 
mutable global goal states for the 
continent that the explorers set out 
to achieve. Rather, the explorers' goals 
evolved with the exploration methods 
as the exploration proceeded. 

Searching problem spaces is limited 
mainly in its applicability to artificial 
domains like chess and mathematical 
theorem proving. It is not very adapt- 
able to the hurly-burly of solving 
problems involving interaction with 
the physical world. Problem spaces 
do not provide sufficient flexibility to 
represent the problem-solving pro- 
cesses of communities because of the 
attempt to represent the problem 
solving of individual actors as a single 
global state. This limitation of prob- 
lem spaces is closely related to the in- 
adequacies of the Hiring machine as 
a model of asynchronous distributed 
systems. Problem solving in open sys- 
tems is more analogous to the ex- 
ploration of North America than the 
playing of games like chess. 

Planner 

Planner was one of the first AI pro- 
gramming languages to support goal- 
oriented problem solving without an 
externally specified problem space. It 
was based on the following principles 
(see reference 6): 



• Accessibility: Planner aims for a max- 
imum of flexibility so that whatever 
knowledge is available can be incor- 
porated into the problem-solving pro- 
cess even if it is fragmentary and 
heuristic. 

• Pattern-directed invocation: Procedures 
in Planner can be invoked by patterns 
of what they are supposed to accom- 
plish. Suppose that we have a 
stopped sink. One way we could try 
to solve the problem would be to 
know the name of a plumber whom 
we could call. An alternative that is 
more analogous to pattern-directed 
invocation is to advertise the fact that 
we have a stopped sink and the quali- 
fications needed to fix it. In Planner 
this is accomplished by making the 
advertisement (i.e., the pattern that 
represents what is desired) into a 
goal. 

• Procedural interpretation of logical state- 
ments: One basic idea behind Planner 



is to exploit the duality that we find 
between certain imperative and 
declarative sentences. Consider the 
statement (implies A B). The state- 
ment is a perfectly good declarative. 
In addition, it can also have certain 
imperative uses for Planner. It can say 
that we might set up a procedure that 
will note whether A is ever asserted 
and if so to consider the wisdom of 
asserting B in turn. Furthermore Plan- 
ner permits us to set up a procedure 
that will watch to see if it is ever our 
goal to try to deduce B and if so 
whether A should be made a subgoal. 
Exactly the same observation can be 
made about the contrapositive of the 
statement (implies A B). Statements 
with universal quantifiers, conjunc- 
tions, disjunctions, etc., can also have 
both declarative and imperative uses. 
Planner theorems are used as im- 
peratives when executed and as 

{continued) 





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APRIL 1985 • BYTE 227 



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228 BYTE • APRIL 1985 



Inquiry 201 



OPEN SYSTEMS 



declaratives when used as data. 

Planner represented an advance 
over the "uniform proof procedures" 
of resolution theorem-proving sys- 
tems then current. The design for 
Planner was implemented by Suss- 
man, Winograd, and Charniak (see 
references 5, 23). Winograd used it to 
implement his interactive natural- 
language program, SHRDLU, for a 
world with simulated toy blocks (see 
reference 27). 

In order to understand how pro- 
cedural interpretation works, consider 
this logical statement: 

(For All x ((man x) implies (mortal x))) 

The implication has two parts: the 
antecedent (man x) and the conse- 
quent (mortal x). It says: For every x, 
if x is a man, then x is mortal. Logical 
rules of inference permit certain 
deductions from the above statement. 
For instance, that Socrates is mortal 
can be derived from the premise that 
Socrates is a man as follows: 

(Man Socrates) 



(Mortal Socrates) 

I proposed that logical implications 
like "all men are mortal" could be in- 
terpreted as procedures in a program- 
ming language. One interpretation, the 
belief-invoked interpretation (called the 
"antecedent interpretation" in Planner), 
provides that when the belief that x 
is a man is held, then the belief that 
x is mortal can be logically derived. 
We can express this as follows: 

(when (belief (man %)) do 
(believe (mortal x))) 

Another interpretation, the goal- 
invoked interpretation (called the "con- 
sequent interpretation" in Planner), 
provides that from the goal that x is 
mortal, the subgoal that x is a man 
can be logically derived: 

(when (goal (mortal x)) do 
(show (man x))) 

The ideas in Planner have been 
generalized and perfected in subse- 
quent artificial-intelligence program- 
ming languages. However, by them- 



selves they do not address the needs 
of open systems. 

Logic Programming 

Logic programming has been pro- 
posed by some as the programming 
paradigm for the future (see reference 
12). Let's focus on limitations that are 
inherent in the enterprise of attempt- 
ing to use logic as a programming lan- 
guage for dealing reliably with em- 
pirical knowledge and interacting with 
the physical world. The remarks in this 
section continue a debate that begins 
with the genesis of AI. 1 recommend 
that interested readers consult the ap- 
pendix to Marvin Minsky's frames 
paper (see reference 1 5) and the sub- 
sequent analysis of David Israel (see 
reference 8). 

Logic programming must be based 
on logic. But what is logic? First-order 
logic, with its well-defined semantics 
and syntax, is the basis claimed by 



most of those who call themselves 
logic programmers. In part, the con- 
fidence of logic programmers is 
based on the fact that first-order logic 
augmented with set theory has 
proved to be a good foundation for 
mathematical semantics. 

Omega-order logic is an extension 
to first-order logic that allows quan- 
tification over predicates and func- 
tions. It has advantages over first- 
order logic in that it includes the full 
lambda calculus as a sublanguage 
and has arbitrary powers of abstrac- 
tion. When certain technical problems 
having to do with Russell's Paradox 
have been dealt with, omega-order 
logic may be the preferred logical lan- 
guage (see reference 19). Therefore, 
we should consider it to be in the 
mainstream of logic programming. 
Experts have argued that the merits 
of other logics can be found in first- 

{continued) 



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APRIL 1985 -BYTE 229 



OPEN SYSTEMS 



order logic (see references 14 and 26), 
so the analysis in this article is con- 
fined to first-order logic without loss 
of generality. 

The Inconsistency Problem 

I make the following claim, which I call 
the Conjecture of Inconsistency: The 
axiomatizations of the human knowl- 
edge of all physical systems are 
uniformly inconsistent in practice. 

I've used the term conjecture because 
the above claim is in principle impos- 
sible to prove rigorously, easy to 
disprove by counterexample, and has 
a preponderance of evidence in its 
favor. The reasons for the inconsisten- 
cy have to do with the dispersed asyn- 
chronous nature of human knowl- 
edge, including the following factors: 

• Environmental context: The physical sys- 
tem being axiomatized is related to 
various other physical systems. For ex- 



ample, a diseased kidney is often 
related to a diseased heart. Knowl- 
edge of the kidney cannot be sepa- 
rated from knowledge of the heart. 

• Spatiotemporal context: A physical sys- 
tem is situated in space and time. 
Knowledge of the physical system 
comprises knowledge of its history 
and mode of production. 

• Terminological context: The predicates 
used in the axiomatization of the 
properties of a physical object are 
always somewhat problematic in prac- 
tice. For example, specifying in prac- 
tice what it means for a physical table 
to be flat raised many problematic 
issues. 

• Evidential context: It is impossible to 
separate what we know about a 
physical object from how we came to 
know it. Axiomatization of the 
methods by which the axiomatized 
knowledge came to be known further 
enlarges the axiomatization. 



The DEC System-20 is a good case 
in point. In the first place observe that 
the DEC System-20 is an extremely 
simple system in comparison with, 
say, the human kidney. Furthermore, 
the DEC System-20 is an artificial 
human construct that was designed to 
be consistent with some simple re- 
quirements. Nevertheless, despite the 
best efforts of software engineers, the 
formal description (axiomatization of 
documentation and code) of the DEC 
System-20 remains inconsistent. 
There are inconsistencies in the docu- 
mentation as well as inconsistencies 
between the documentation and the 
code. Although inconsistencies are 
continually being removed from the 
system, the experience is that more 
inconsistencies are always found 
immediately. 

Suppose that we were given un- 
limited funding to undertake the job 

{continued) 



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Inquiry 143 for Dealers. 
Inquiry 144 for End Users. 



OPEN SYSTEMS 



of making the description of the DEC 
System-20 consistent. We would have 
to control the process by which the 
system grows and evolves. In par- 
ticular, we would have to handle all 
changes to the documentation and 
code in face of the following external 
requirements: 

• Bugs in both the code and docu- 
mentation must be fixed 

• New functions must be incor- 
porated to meet the customers' 
changing needs 

• The system must accept changing 
interfaces to other systems such as 
peripherals and networks 

There is no way to prove that the 
process by which the DEC System-20 
evolves will result in new releases with 
consistent formal descriptions. An ax- 
iomatization of the code and docu- 
mentation of even a system as simple 



as the DEC System-20 is, in practice 
inconsistent despite enormous efforts 
made to achieve consistency 

A second claim I make is that the 
axiomatizations of the human knowl- 
edge about any physical systems will 
forever be inconsistent. 1 call it the 
Conjecture of Perpetual Inconsisten- 
cy: Removing some inconsistencies 
from an axiomatization of the human 
knowledge about a physical system 
leaves an axiomatization which is 
nevertheless inconsistent. 

Message -Passing Semantics 

Consideration of the previous claim 
suggests that we need to examine 
how logic treats inconsistency. Incon- 
sistencies have some important im- 
plications of the utility of logic pro- 
gramming as a foundation for intelli- 
gent systems. The logical view of in- 
consistent theories is clear: They are 
meaningless because they corre- 



spond to no possible world. The 
logical account of meaning is too 
stringent for nontrivial empirical 
systems because inconsistent beliefs 
and descriptions are not meaningless. 
Inconsistency is inherent in the enter- 
prise of expressing the human knowl- 
edge of physical systems. A theory of 
meaning that maintains that inconsis- 
tent descriptions are meaningless is 
not directly applicable to problems of 
empirical knowledge 

In model theory, the meaning of a 
sentence is determined by the models 
that make it true (see reference 24). 
For example the conjunction of two 
sentences is true exactly when both 
of its conjuncts are true TYuth- 
theoretic semantics assumes that it is 
possible to give an account of truth 
in itself, free of interactional issues, 
and that the theory of meaning can 
be based on such a theory of truth. 

{continued) 



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APRIL 1985 'BYTE 233 



OPEN SYSTEMS 



Message-passing semantics takes a 
different perspective on the meaning 
of a sentence: It takes the meaning of 
a message to be the effect it has on 
the subsequent behavior of the sys- 
tem. In other words, the meaning of 
a message is determined by how it af- 
fects the recipients. Each partial 
meaning of a message is constructed 



by a recipient in terms of how it is pro- 
cessed (see reference 12). At a deep 
level understanding always involves 
categorization, which is a function of 
interactional (rather than inherent) 
properties using the perspective of in- 
dividual viewpoints (see reference 13). 
Meaning is thus fundamentally inter- 
actional. The meaning of a message 



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is open-ended and unfolds indefinite- 
ly far into the future as other reci- 
pients process the message. Accord- 
ing to message-passing semantics, 
meaning is communication-based, not 
logic-based. 

Need for Due-Process 
Reasoning 

In the presence of conflicting informa- 
tion and contradictory beliefs, logical 
proof is inadequate as a reasoning 
mechanism. Instead we need due- 
process reasoning that investigates dif- 
ferent sides of beliefs, goals, and 
hypotheses that arise. 

Consider the following hypothesis 
to illustrate due-process reasoning: 
"Nixon was guilty of destruction of 
evidence in the Watergate case by 
erasing a portion of a tape recording." 
One possible approach in logic pro- 
gramming is to gather evidence in 
favor of the hypothesis and attempt 
to fashion the evidence into a logic 
proof (perhaps augmented with "cer- 
tainty factors" or "default assump- 
tions"). The other approach is to use 
"negation as failure" to conclude that 
the hypothesis is false because it can- 
not be proved from the available 
knowledge. Both of the approaches 
are inadequate in this case. No mat- 
ter how much evidence is produced 
and analyzed, logical proof (either for 
or against Nixon's guilt) is unbalanced 
because it presents only one side of 
the case in the form of a proof. Using 
"negation as failure" to draw conclu- 
sions from the inability to construct 
such a proof is equally limited. A 
balanced approach requires debate 
between differing positions and 
weighing presented evidence. 
Debates are not structured in the 
same way as logical proofs. 

Due-process reasoning is the pro- 
cess of collecting and analyzing the 
evidence and arguments presented 
by all interested parties. Advocates col- 
lect evidence and organize arguments 
in favor of the hypothesis. In parallel, 
skeptics collect evidence and organize 
arguments against the hypothesis. 
Then a debate is conducted on 
grounds for deciding the case in 
terms of motive and ability. The ques- 



234 BYTE' APRIL 1985 



Inquiry 1 6 



OPEN SYSTEMS 



tion of motive is whether Nixon 
thought that he would benefit by eras- 
ing the tape. The question of ability 
is whether he could have erased the 
tape Both advocates and skeptics 
recursively make use of due-process 
reasoning while investigating, organiz- 
ing, and presenting their cases. The 
advocates and skeptics operate inter- 
dependent^ in collecting evidence 
(through discovery processes and 
disclosure requirements) as well as in- 
teracting by debating each others' 
cases in a decision-making process 
that is fundamentally different from 
logical proof. 

Prolog 

Advocates of logic programming ini- 
tially developed a programming lan- 
guage called Prolog that was based 
on the goal-invoked procedural inter- 
pretation of implication discussed 
earlier in the section on Planner (see 
reference 11). The example discussed 
earlier to the effect that "In order to 
show that x is mortal, establish a 
subgoal to show that x is a man" is 
written in Prolog as: 

mortal (x) :- man (x) 

The original Prolog was a much 
simpler language than Planner, which 
was a considerable advantage in 
terms of pedagogy and ease of imple- 
mentation. But now Prolog, like the 
Planner-like languages before it, has 
fissioned into incompatible dialects 
based on the procedural interpreta- 
tion of logic, pattern-directed invoca- 
tion, message-passing theory, and de- 
scription systems (see references 4, 9, 
and 12). 

In addition to the general limitations 
of logic programming discussed 
earlier, Prolog has some idiosyncratic 
weaknesses all its own. The closed- 
world assumption is the hypothesis 
that the locally available knowledge 
is complete; i.e., if a proposition does 
not follow from the local knowledge 
base, then it is assumed to be false 
(see reference 18). Planner could 
make use of the closed-world assump- 
tion using its ability to conditionalize 
a plan (theorem) on the exhaustive 

{continued) 



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OPEN SYSTEMS 



failure to establish a goal. In fact, 
Winograd made strong use of the 
capability in SHRDLU. Influenced by 
Planner, Prolog went much further 
and adopted a very strong form of the 
closed-world assumption as a basic 
postulate of the programming lan- 
guage in incorporating negation as 
failure. (Relational database systems 
make use of a similar strong hypothe- 
sis: If an entry is not found in a rela- 
tional table then the relationship is 
false.) The strong use of the closed- 
world assumption in Prolog is incom- 
patible with the need in open systems 
to allow for the open-ended in- 
cremental introduction of new beliefs 
and objects. 

Information-Processing 
Principles for the Future 

The term reflection has been much 
discussed in the current AI literature 
(see references 2, 4, 7, 22, and 26). 
It is universally conjectured that 
reflective problem capabilities will be 
important to improving machine 
problem-solving capabilities. How- 
ever, a danger is developing that the 
important problems will be neglected 
unless reflective problem solving is 
taken to encompass the following 
minimum capabilities: 

• History of its own behavior. What did 
you do then? 

• Representation of its own information- 
processing procedures: How do you make 
decisions? 

• Knowledge of the relationship between its 
previous behavior and current procedures: 
What would you do differently and 
why? 

• Representation of its procedures for inter- 
acting with the external world: How do you 
control things? 

The current state of the art in imple- 
menting reflective systems is extreme- 
ly primitive. Many of the issues and 
questions itemized above have not 
yet been properly addressed. 

Besides reflective problem solving, 
other principles should be adopted in 
constructing reliable systems that 
meet the needs of open systems. 

[continued) 



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APRIL 1985 'BYTE 237 



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OPEN SYSTEMS 



• Serendipity: It is not critical whether 
the system learns of a result before 
it can be used in a problem-solving 
task or after work has commenced on 
the task. 

• Pluralism: There is no central arbiter 
of truth in the system. 

• Accessibility: All knowledge of the sys- 
tem (including its own procedures) 
should be able to be applied to any 
problem. 

• Parallelism: The system should be 
able to mobilize its full resources in 
parallel instantiations for different 
aspects of large-scale problems. 

• Due-process reasoning: The system col- 
lects and debates alternatives to 
decide among beliefs and goals. 

• Reflection in practice: Knowledge (in- 
cluding self-knowledge) should inform 
practice, and practice should modify 
hypotheses, beliefs, and goals. 

• Reasonableness: The system should 
perform efficiently in the face of con- 
flicting information and inconsistent 
beliefs. 

Conclusions 

In practice, the human knowledge of 
a physical system cannot be con- 
sistently axiomatized. Every physical 
system is open in the sense that it is 
embedded in a larger physical en- 
vironment with which it interacts asyn- 
chronously In general, open systems 
are not totally in control of their fate. 
In contrast, closed systems (like Peano 
arithmetic and point-set topology) are 
exactly characterized by rules and 
laws. 

Proponents of logic programming 
have maintained that it is a suitable 
basis for all programming and is the 
programming paradigm for the future. 
Logic programming has some funda- 
mental limitations that preclude its 
becoming a satisfactory programming 
methodology. It is inadequate for the 
needs of open systems because it is 
based on logical operations instead 
of communication primitives and 
logical reasoning instead of due- 
process reasoning. Decisions in open 
systems are justified by agreements to 
act in certain ways. Justification by 
agreement stands in contrast to justi- 

{continued) 
<* — Inquiry 342 



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OPEN SYSTEMS 



fication by logical proof; interaction 
with the physical world involves deal- 
ing with conflicting and contradictory 
information in a way that does not fall 
within the scope of decision making 
by logical proof. Prolog also suffers 
from the limitation of "negation as 
failure," restricting it to a closed-world 
assumption that is incompatible with 
the nature of open systems. 

We need foundations for intelligent 
systems based on principles of com- 
mutativity pluralism, accessibility 
reflection in practice, and due-process 
reasoning. Logical reasoning is a 
useful module in the repertoire of an 
intelligent system, but it is not the 
whole show. ■ 

ACKNOWLEDGMENTS 
Many of the ideas in this paper have been 
developed jointly with the members of the 
MIT Message Passing Semantics Group 
and the TVement Research Institute. I 
would especially like to express my ap- 
preciation to Gul Agha, Gerald Barber, 
Peter de Jong, Elihu M. Gerson, and Susan 
Leigh Star for their aid and the founda- 
tional work on which this paper builds. 
Jonathan Amsterdam, Mike Brady Mike 
Brooks, Toni Cohen, Peter de long. John 
Kam, Henry Lieberman, John Maliery 
Fanya Montalvo, Karen Prendergast 
Claudia Smith, and John Teeter provided 
valuable comments and criticisms that 
helped greatly to improve on earlier drafts. 
Over many years I have benefited from ex- 
tensive interactions with Richard 
Weyhrauch, who has a profound under- 
standing of the issues discussed here. 

The content of this paper comes from 
talks I have given at Stanford University 
in June 1983, at panels for IFIP-83 in Paris, 
at the MIT Artificial Intelligence Lab- 
oratory in November 1983, at BBN, at MIT 
Sloan School, and at the AAAS in New 
York during June 1984. Comments, 
criticisms, and arguments developed in 
these seminars have been invaluable in 
developing this paper. I would like to ex- 
press special appreciation to Bob Moore 
Nils Nilsson, Steve Hardy Richard 
Waldinger, and others for valuable feed- 
back during and after the Stanford 
seminar; Bob Kowalski and Doug Ross at 
the IFIP-83 panel; Jan Komorowski at the 
MIT seminar; David Israel at the BBN 
seminar; Tom Malone and Gerald Barber 
at the Sloan School seminar; as well as 
Victor Lesser, Jerry Hobbs, and Lucy 

{continued] 



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Suchman at the AAAS session. Allen 
Newell took the time to give me an over- 
view of some of the aspects of his recent 
work on foundations in July 1984. 

This paper describes research done at 
the MIT Artificial Intelligence Laboratory. 
Major support for the research reported 
in this paper was provided by the System 
Development Foundation and Wang 
Laboratories. Major support for other 
related work at the Artificial Intelligence 
Laboratory is provided, in part, by the Ad- 
vanced Research Projects Agency of the 
Department of Defense under Office of 
Naval Research contract N0014- 
80-C-0505. I would like to thank Charles 
Smith and Patrick H. Winston for their sup- 
port and encouragement. 

REFERENCES 

1. Agha, Gul. "Semantic Considerations in 
the Actor Paradigm of Concurrent Com- 
putation." Proceedings of the NSF/SERC 
Seminar on Concurrency. New York: Springer- 
Verlag, 1984. 

2. Batali, J. "Computational Introspection." 
AI Memo 701. Cambridge. MA: MIT Ar- 
tificial Intelligence Laboratory. February 
1983. 

3. dinger, W D. "Foundations of Actor 
Semantics." AI-TR-633. Cambridge, MA: 
MIT Artificial Intelligence Laboratory, May 
1981. 

4. Doyle, J. "A Model for Deliberation, Ac- 
tion, and Introspection." AI-TR-581. Cam- 
bridge, MA: MIT Artificial Intelligence 
Laboratory. 1980. 

5. Hewitt, C. "PLANNER: A Language for 
Proving Theorems in Robots." Proceedings 
of IJCAI-69. Washington, DC: IJCAI. May 
1969. 

6. Hewitt, C. "Description and Theoretical 
Analysis (Using Schemata) of PLANNER: 
A Language for Proving Theorems and 
Manipulating Models in a Robot." 
AI-TR-258. Cambridge, MA: MIT Artificial 
Intelligence Laboratory, April 1972. 

7. Hewitt C, and P. de Jong. "Analyzing 
the Roles of Descriptions and Actions in 
Open Systems." Proceedings of the National 
Conference on Artificial Intelligence, AAA1, 
August 1983. 

8. Israel, D. A Short Companion to the 
Naive Physics Manifesto" In Formal Theories 
of the Common Sense World, I. Hobbs, ed. 
Abelex. 1984. 

9. Kahn, K. "How to Implement Prolog on 
a LISP Machine" In Implementations of Pro- 
log, Campbell, J. A., ed. New York: John 
Wiley & Sons, 1984, pages 117-134. 

10. Kornfeld, W. A., and C Hewitt. "The 
Scientific Community Metaphor." IEEE 
Transactions on Systems, Man, and Cybernetics. 



SMC-11, 1. January 1981. 

11. Kowalski, R. A. "Predicate Logic as Pro- 
gramming Language." Proceedings of 1 T1P-74 . 
IFIP, 1974. 

12. Kowalski. R. A. In The SIGART Special 
Issue on Knowledge Representation, R. Brachman 
and B. Smith, eds. SIGART, 1978. 

13. Lakoff, G., and M. Johnson. Metaphors 
We Live By. Chicago: University of Chicago 
Press. 1980. 

14. McCarthy, J. "First Order Theories of 
Individual Concepts and Propositions." 
Stanford. CA: Stanford University Press, 
July 1977. 

1 5. Minsky, M. "A Framework for Repre- 
senting Knowledge." In The Psychology of 
Computer Vision, Winston, P., ed. New York: 
McGraw-Hill, 197 5. 

16. Newell, Allen. "Reasoning, Problem 
Solving, and Decision Processes: The 
Problem Space as a Fundamental 
Category." Technical Report CMU-CS-79-I33. 
CMU, June 1979. 

17. Reddy, M. "The Conduit Metaphor." In 
Metaphor and Thought, Ortony, A., ed. Cam- 
bridge: Cambridge University Press, 1979. 

18. Reiter, R. "On Closed World Data 
Bases." logic and Data Bases. New York: 
Plenum Publishing Corp.. 1981. 

19. Rudin. L. "Lambda-Logic." Technical 
Report 4521. Pasadena, CA: California In- 
stitute of Technology, May 1981. 

20. Selfridge, O. "Pandemonium: A 
Paradigm for Learning." Technical Report 
JA-1140. Cambridge: MIT. 1958. 

21. Shapiro, E. "A Subset of Concurrent 
Prolog and Its Interpreter." Technical Report 
TRO03. 1COT, January 1983. 

22. Smith, B. "Reflection and Semantics in 
a Procedural Language." LCS-TR-272. 
Cambridge, MA: MIT Laboratory for 
Computer Science, 1982. 

23. Sussman, G. J., T. Winograd, and E. 
Charniak. "MICROPLANNER Reference 
Manual." A! Memo 203. Cambridge, MA: 
MIT Artificial Intelligence Laboratory, 
1970. 

24. Tarski, A. "The Semantic Conception 
of Truth." Philosophy and Phenomenological 
Research 4 (1944). pages 341-375. 

2 5. van Emden, M., and R. Kowalski. "The 
Semantics of Predicate Logic as a Pro- 
gramming Language." J ACM 23, No 4 
(1976), pages 733-742. 

26. Weyhrauch. R. "Prolegomena to a 
Theory of Mechanized Formal Reasoning." 
Artificial Intelligence 13, 1, 2 (April 1980), 
pages 133-172. 

27. Winograd, T "Procedures as a Repre- 
sentation for Data in a Computer Program 
for Understanding Natural Language." 
Cambridge, MA: MIT Project MAC, MAC 
TR 83, 1971. 



242 B YTE • APRIL 1985 



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ARTIFICIAL INTELLIGENCE 



VISION 



by Dana H. Ballard and Christopher M. Brown 



Biology challenges technology 



VISION AND MOTOR CONTROL are 
such common capabilities in the 
animal kingdom that we do not usual- 
ly associate them with intelligence. Yet 
vision has always been a paradigm 
problem for artificial intelligence (AI), 
since it is mysteriously difficult. Tech- 
nology has mounted many responses 
to the biological challenge of reliable, 
versatile, real-time vision systems, but 
so far the resulting industrial systems 
only work in specialized settings (or 
domains). These systems are routinely 
used to inspect integrated circuits and 
manipulate parts but cannot be used 
outside of these limited contexts. For 
example, the systems' image input is 
binary (black and white), not the full 
gray-scale range provided by an input 
device such as a TV camera. Attain- 
ing such an image calls for carefully 
engineered lighting and imaging con- 
ditions. Also, to attain the necessary 
speed, the systems have simple algo- 
rithms that will not tolerate events 
such as parts obscuring one another 
or lying propped up at odd angles. A 
seemingly simple but elusive in- 
dustrial vision task, beyond the capa- 
bility of all current systems, is the "bin- 
picking" problem, one regularly sur- 
mounted by humans; It involves sim- 



ply grasping and removing parts 
jumbled together in a bin, not laid out 
flat on a special surface. 

Thus, fast, reliable computer vision 
is so hard that we can presently 
achieve it only in highly constrained 
and simplified domains. This makes 
the fast and reliable vision performed 
by biological systems all the more 
marvelous and mysterious. Somehow, 
humans perform recognition, descrip- 
tion, manipulation, and locomotion in 
a highly complex world of moving 
solid objects, both rigid and nonrigid, 
with complex (textured, transparent, 
glossy, etc.) surfaces and highly 
variable illumination conditions. 

General-purpose vision systems, 
which can build descriptions of their 
environment in general situations, re- 
main a research goal. Today, a consen- 
sus is emerging that such systems will 
be designed around two central ideas, 
originating in biology and redis- 
covered by researchers in technology. 
The embodiment of these ideas in vi- 
sion systems is a topic of much cur- 
rent concern and an area of rapidly 
expanding technological achievement 
and biological insight. 

The first idea is that vision systems 
use a hierarchy of representations 



that develops visual information in 

many intermediate stages to span the 
gap from input signal to cognitive 
symbols. Computer-vision researchers 
found the hierarchy to be a solution 
to several technical problems of com- 
puting and storage efficiency. Current- 
ly, researchers in the neurosciences 
are studying the extent of such a func- 
tional and physiological hierarchy in 
biological systems, and many signs 
point to biological versions of the 
computer-vision hierarchy. 

The second idea is parallel com- 
putation. Researchers have known for 
a long time that nervous systems com- 
pute in parallel, and they have made 
many attempts to model such com- 
putations. Recent work has provided 
new tools in these areas (see the ar- 
ticles in this issue "Learning in Parallel 
Networks" by Geoffrey E. H in ton on 
page 265 and "Connections" by 
Jerome A. Feldman on page 277) and 
powerful parallel computing engines 
are now realizable. In the remainder 

[continued) 
Dana H. Ballard is an associate professor and 
Christopher M. Brown is the chairman of the 
Department of Computer Science. University 
of Rochester (Ray P. Hylan Building, 
Rochester, NY 14627). 



«« — Inquiry 363 



APRIL 1985 -BYTE 245 



VISION 



of this article, we will explore the two 
themes of representational hierarchy 
and parallelism in computational and 
biological vision. 

History and Background 

The digital analysis of visual input has 
been a research issue since the late 
1950s when computers became large 



enough to accommodate such data. 
After about a quarter of a century of 
development, computer vision is a 
large subfield of AI. Like robotic con- 
trol and computer-speech analysis, 
computer vision often uses "real" 
data—that is, the raw output of 
sensors— as its input. However, com- 
puter vision also uses more symbolic 



c 



OBJECT. SCENE, EVENT RECOGNITION 



) 



SCENE DATA STRUCTURES 

FACES. EDGES. VERTICES 

OBJECT BOUNDARIES 

VOLUMES 

SPATIAL RELATIONS 



THREE-DIMENSIONAL ANALYSIS 
SEGMENTATION 
INTERPOLATION 
BOUNDARY AND OBJECT DETECTION 



DATA STRUCTURES 
REGIONS 
LINES 
SPATIAL RELATIONS 



PHYSICAL PROPERTY IMAGES 

SURFACE ORIENTATION 

MOTION 

STEREO FUSION 

REFLECTANCE 

DEPTH 



TWO-DIMENSIONAL ANALYSIS 
FEATURE -FINDING 
SIMPLE GROUPING 
IMAGE SEGMENTATION 



( IN 



TRINSIC IMAGE CALCULATION 



) 



IMAGE(S) 

COLOR OR GRAYSCALE INFORMATION. 
POSSIBLY TIME -VARYING 



SCALING AND CORRECTION 

IMAGE PREPROCESSING 
NOISE REMOVAL 
CONTRAST ENHANCEMENT 
GAMMA CORRECTION 



SENSING 

TV INPUT 

DIGITIZATION 
REMOTE SENSING 



Figure 1: The processes (ellipses) and data representations (rectangles) of a general 
computer-vision system. Processing can proceed from input data to symbolic description 
(a normal data-driven scheme] or in the reverse direction [where expectations guide 
processing). Control is most often thought to flow in both directions. Each stage of 
processing includes assumptions about how the image information is related to the 
phenomena of interest in the world. In natural systems these assumptions may be 
innate or learned. 



246 BYTE • APRIL 1985 



or processed data. Thus, one vision 
program can have, for example, an ar- 
ray of gray-level intensities from a 
television image as input, while an- 
other program may take a symbolic 
description of a line drawing as input. 

The goals of computer vision are also 
diverse but may be characterized as 
seeking answers to "what," "where," 
and "why" questions. "What" ques- 
tions concern the identification of ob- 
jects in a scene; "where" questions in- 
volve the perception of the environ- 
ment in time and space; and "why" 
questions address causal relation- 
ships between objects. 

Thae computer vision, with the goal 
of understanding images of complex 
three-dimensional scenes, was first at- 
tempted in the early 1960s by Larry 
Roberts at MIT (see reference 1). His 
goal was to "understand" a scene 
made up of polyhedral blocks, in the 
sense of being able to produce a line 
drawing of the scene from any view- 
point. Roberts's system pioneered 
many fundamental techniques still in 
use today, not just in computer vision, 
but also in computer graphics. In par- 
ticular, the system analyzed digitized 
input images by identifying "edge 
elements" that might line up along the 
polyhedral edges (see figure 3 b for an 
illustration of this technique in 
another application). The system then 
fused these edge elements to pro- 
duce longer lines that corresponded 
to the polyhedral edges (figure 3 c 
again is similar) and matched the 
resulting line and polygon data struc- 
tures against three-dimensional 
models of primitive blocks. This pro- 
cess derived the scaling, rotation, and 
translation of the models needed to 
explain the image data, and this infor- 
mation allowed the system to produce 
the final line drawings, using basic 
computer-graphics techniques— also 
first attempted by Roberts— such as 
hidden-line removal. 

Roberts's goal was ambitious even 
by today's standards: No computer vi- 
sion system will perform the task of 
reliably identifying blocks on a table 
in the presence of occlusion and 
noise. However, such early work 

{continued) 

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VISION 



revealed the immense computational 
complexity of vision and the unreli- 
ability and inadequacy of sequential 
control structures to allocate process- 
ing power. 
Such a task requires an extraordi- 



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includes extracting physical informa- 
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///lit 
f t / / I I 
/ / / / I I 
f / / / / I 
t / t f / / 
/ / f ( f i 
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I V V v 

V v \ t 

V \ \ X 

V \ \ N 

V V V \ 

\ \ \ K 

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'''/// I 

' ' ' i $ i i \ 

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+ * * S A / / / 
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Figure 2a: Optic flow images (retinal pattern velocities caused by scene motion) from 
a rotating sphere and cylinder. 



Thus the field of computer vision is 
quite large. It includes the afore- 
mentioned industrial inspection sys- 
tems, as well as academic research ef- 
forts whose competence (what we 
must know to solve a problem) is 
often of more interest than their per- 
formance (how we actually solve the 
problem in real time). See the biblio- 
graphy at the end of this article for 
more material on the field of com- 
puter vision. 

in the 1970s a cognitive approach 
to computer vision arose, which con- 
veniently minimized image-level com- 
putation and emphasized the sym- 
bolic manipulations to which com- 
puters are well adapted. In such 
"knowledge-directed" vision, process- 
ing uses facts about such phenomena 
as gravity, support, occlusion, or the 
likely spatial relations between ob- 
jects in the scene. Research turned 
toward representing and manipulating 
facts about a particular setting (or do- 
main, such as a grouping of polyhedral 
blocks or an office scene) and exploit- 
ing the domain-specific knowledge in 
vision. 

However, the representation and 
application of knowledge is a very dif- 
ficult branch of AI, and the available 
techniques proved inadequate to 
bridge the gap between the input 
image and the desired symbolic de- 
scriptions of it. Thus in 1974, starting 
with Marr at MIT and Barrow and 
Tenenbaum at Stanford Research In- 
stitute, attention was directed toward 
a collection of intermediate represen- 
tations, termed intrinsic images, that 
would span the representation gap. 

Today, the consensus of the com- 
puter-vision community is that this 
gap is bridged by a set of visual data 
representations that are arranged in 
a hierarchy of increasing abstraction. 

Vision and 

the Abstraction Hierarchy 

Our vision is quite reliable— that is, 
there is a good correlation between 
our perceptions and things in the 
world. Otherwise, we would not have 
survived as a species. How do we ig- 
nore irrelevant variations and concen- 
trate on those that mean something? 



248 B YTE • APRIL 1985 



VISION 



How do we achieve the constancies 
whereby we recognize objects under 
varying illumination, or faces at dif- 
ferent ages? How do we perform so 
fast and reliably? A partial answer to 
these questions is that of abstraction 
hierarchies. 

Modern computer vision spans the 
gap between input image and object 
perception with a hierarchy of repre- 
sentations (the aforementioned intrin- 
sic images) operated on by powerful 
computational processes (as shown in 
figure 1). These processes create 
representations that pass from image- 
like representations of physical 
parameters to symbolic descriptions. 
Constructing these intermediate 
descriptions is feasible and probably 
necessary, but it involves complex 
computations for a general vision sys- 
tem (as opposed to a highly spe- 
cialized system, such as an industrial 
system). 

At the earliest level (the input level), 
a general vision system derives a rep- 
resentation of image brightness 
changes that it uses for stereo dispari- 
ty calculations (the difference be- 
tween two views of the same setting), 
detecting changes in surface composi- 
tion, orientation, distance, reflectance 
and so forth. Perceptual phenomena 
(e.g., subjective contours, the ability 
to discern colinearity of dissimilar 
shapes) suggest components for the 
earliest image representations (e.g., 
locations, orientations, and endpoints 
of features). Feature detectors that 
derive these components may then 
be designed by humans. 

Much current research is centered 
around the production of physical 
property images, which are inter- 
mediate representations that the sys- 
tem forms before attempting object 
recognition. These image-like repre- 
sentations are registered with the in- 
put image and contain values of 
physical parameters of scene points 
such as the distance from a sensor to 
the point, the albedo (reflective 
power) of surfaces, the objects' direc- 
tion of motion, the location of 
shadows and light sources, and so 
forth. Researchers generally assume 
that the processes producing physical 



property images are part of 'early vi- 
sion." That is, they are not dependent 
on the context of the scene being 
viewed, much less on conscious rea- 
soning, but are robust general pro- 
cesses that produce reliable output in 



a broad range of natural circum- 
stances. However, these processes 
cannot be completely general and 
reliable, since the two-dimensional in- 
put image does not capture three- 

[continued) 




Figure 2b; Shapes causing the images as derived by a computational vision process. 
Such processes use mathematical models of physical laws and assumptions about nature 
to recover physical information about scenes from input images. \Courtesy of John 
Aloimonis, University of Rochester.] 



APRIL 1985 -BYTE 249 



VISION 



dimensional information directly (it 
can only imply it). But the usual 
reliability of these processes in animal 
vision implies that they rely on natural 
constraints or assumptions about the 
world to derive unambiguous output. 
Identifying and using such constraints 
are important goals of modern com- 
puter-vision research. This, in turn, 
calls for seeking out properties of the 
physical work that could help a visual 
process do useful work, making math- 
ematical models of their interaction 
with visual phenomena, and imple- 
menting the mathematics in computer 
programs. One such result that illus- 
trates the kind of computations at this 
level is the computation of relative 
depth from optic flow (see figure 2). 
The step beyond intrinsic images is 
a large one; although they contain 
physical information, they are still 
image-like entities not yet described 
in terms of objects. Two of the most 
important visual phenomena are mo- 
tion and texture, which transmit much 
information about the objects and 
surfaces in a scene. One of the most 
active areas of computer-vision 
research is the extraction of informa- 
tion from motion or from optic flow 
of the visual field on our retina as an 
object or the viewer moves. It is also 
a particularly good illustration of the 
symbiosis that can take place between 



psychology and computer vision. 

Researchers basically agree that the 
higher abstraction levels in a general 
computer-vision system must contain 
data structures representing aspects 
of the domain from which the scene 
originates. The resulting problems in 
knowledge representation are inter- 
esting in a wide variety of AI applica- 
tions. For example, computer model- 
ing of three-dimensional rigid solids 
is by no means a solved problem ex- 
cept for certain manufactured objects. 
Also, representing naturally occurring 
shapes and volumes so that they can 
be matched to their geometric 
counterparts in intrinsic images is still 
an open question. 

High abstraction levels pose several 
other difficulties. Perception goes on 
through time, and yet representing 
processes through time is an area of 
advanced Al research. 

The contribution of high-level 
knowledge and inferential procedures 
to the vision process is still a mystery. 
It seems certain that information does 
not simply flow "bottoms up" (that is, 
sequentially from low-level to high- 
level) through the visual system, as it 
did in Roberts's first system. Nor is vi- 
sion merely controlled hallucination, 
with the abstract representations dic- 
tating our perceptions as they do in 
dreams, subject to minor corrections 



from incoming data. The upper levels 
of abstraction hierarchy must support 
information flow in both directions, 
and a bottleneck in current computer- 
vision research is achieving useful in- 
teraction between the lower, image- 
like representations and the higher, 
symbolic ones. 

State-of-the-Art Examples 

Two examples will illustrate the opera- 
tion of computer vision in the sort of 
abstraction hierarchy introduced in 
the last section. The three-dimen- 
sional MOSAIC system at Carnegie- 
Mellon University, developed by 
Marty Herman and T&keo Kanade, can 
reconstruct three-dimensional repre- 
sentations of buildings from two aerial 
views— using stereo to provide depth 
information— or from a single view- 
using advance knowledge about the 
nature of the input scene to provide 
depth information. Figures 3a through 
3d show the operation of the mono- 
cular version of the algorithm. 

The MOSAIC system uses an edge 
operator to find intensity discon- 
tinuities, which contain much image 
information in a single input image 
(see figure 3a). Because the image has 
a baffling number of such "edge 
elements," the system sends the out- 
put to a post-processing routine that 
identifies edges that are likely to con- 




Figure 3a: Aerial view of a city park and buildings provided 
as a single input image to the MOSAIC {see text) system. 



Figure 3b: Output of an edge-finding algorithm applied to the 
image of figure 3a. 



250 BYTE • APRIL 1985 



VISION 



tribute to interesting structures in the 
image (see figure 3b). Several stages 
of processing then link the edges into 
two-dimensional structures using stan- 
dard edge-linking technology and in- 
formation about the way lines meet 
to form vertices in polyhedral scenes. 
And then the edges are linked into 
three-dimensional structures— using 
information about gravity support, 
the perspective imaging process, and 
other facts describing the physical 
scene domain and the optics of image 
formation. Figure 3c shows the result 
of this processing: a perspective view 
of a three-dimensional "wireframe" 
representation of edges in the scene. 

The next stage of processing relates 
the wireframes to stored representa- 
tions of three-dimensional solid 
models. In a sense, the solid models 
are the final output of the program, 
with two important additions. First, 
the system can relate new image in- 
formation to its existing model data 
structures, which it can refine as it ac- 
quires the new images. Second, the 
system can, using standard computer- 
graphics technology, map the flat 
image onto the surfaces of the stored 
three-dimensional models. The sys- 
tem can then display three "painted" 
models from another angle, as shown 
in figure 3d. 

Work continues on the extraction 



and identification of meaningful parts 
of an image. This process is called 
segmentation, which is typified in the VI- 
SIONS (Visual Integration by Seman- 
tic Interpretation of Natural Scenes) 
system at the University of Massachu- 
setts. The VISIONS system's sophisti- 
cated programs use models of a 
specific domain (rural, outdoor 
scenes of houses, trees, etc.) and 
knowledge about that domain. 

In this work, the goal is to segment 
a color image (as in figure 4a) into 
regions that correspond to meaning- 
ful objects or substances in the image. 
The process involves extracting 
straight lines (see figure 4b), and 
regions of related color characteristics 
(see figure 4c). The VISIONS system 
uses interpretation rules that incor- 
porate knowledge about the scene 
domain (for example, that a driveway 
is not found silhouetted against the 
sky, or that a house's roof is above its 
walls) in cooperation with the image- 
guided segmentation processes. 
These interpretations make the 
segmentation process more reliable, 
by indicating, for example, when 
regions may be merged or should be 
split. For example, in figure 4c the 
system has colored regions that it has 
hypothesized, using interpretation 
rules, to be shutters. Foliage is an im- 
portant component of these scenes, 



and VISIONS has a set of feature ex- 
tractors and recognizers to allow 
reliable identification of foliage, 
despite its many different ap- 
pearances. 

Figure 5 shows the final labeling of 
another input scene with regions 
identified as sky, foliage, grass, wall, 
shutters, roof, and regions (in black) 
that are uninterpreted due to the lack 
of a symbolic model in the current 
system or deviation of the scene's ap- 
pearance from that predicted by the 
model. VISIONS currently models 
some 20 major objects and object col- 
lections such as "house" and "house 
scene," and a larger number of object 
parts such as "roof" and "shutters." 

The two examples of current sys- 
tems show the beginning of under- 
standing the competence issues in vi- 
sion: We know what kinds of entities 
need to be computed. However, each 
of these examples requires huge 
amounts of computer time. Most re- 
searchers believe that the perfor- 
mance problem in vision will only be 
solved through parallel computation. 

Challenges 

from Animal Vision 

One of the most promising directions 
for the study of parallel processing 
has centered around studies of 

[continued) 



V ~~J^ \ 








Figure 3c: A "wireframe" of linked line segments in three 
dimensions resulting from several sorts of processing applied to 
the data of figure 3b. 



Figure 3d: Computer-graphics techniques use the original photo 
and the three-dimensional models extracted by further processing 
of the wireframe data of figure 3c. resulting in a convincing 
reconstruction of the scene: \Courtesy of Marty Herman and 
Takeo Kanade at Carnegie-Mellon University.] 



APRIL 1985 'BYTE 251 



VISION 



human and animal vision. Unlike 
robot vision, where many of the com- 
plexities of sensing the environment 
can be manipulated by tailoring the 
environment and using special imag- 
ing techniques, animal vision must 
somehow analyze time-varying photo- 
metric data in its full complexity in 
real time. Furthermore, biological sys- 
tems use neural-processing elements 
that are six orders of magnitude 
slower than silicon components. 
Despite all these apparent disad- 



vantages, animal systems succeed ad- 
mirably. Experiments with human 
subjects show that they can make a 
variety of behavioral responses to 
visual stimuli in a few hundred milli- 
seconds. Thus, the biological system, 
somewhat embarrassingly, embodies 
solutions to problems that still plague 
vision researchers. This situation has 
lured researchers to tackle the prob- 
lem of modeling the human visual sys- 
tem head-on, in the hopes of dis- 
covering its secrets. Such researchers 




(4a) 




(4b) (4c) 

Figure 4: [a) An outdoor scene to be analyzed by the VISIONS computer-vision 
system, (b) Straight lines extracted from the data of 4a. (c) Regions extracted from the 
data of 4a. 



typically have a wide range of cross- 
disciplinary interests and are joining 
to make progress in the separate 
fields of psychology, neuroscience, 
and computer science. We shall 
describe some of the more interesting 
of the many new results from these 
disciplines. 

Since humans are very good at 
visual tasks, researchers were sur- 
prised to find that, for some tasks, in- 
formation can be processed in 
parallel, but for rather modest in- 
creases in complexity, the processing 
became sequential (see reference 2). 
Tteisman describes visual displays of 
letters about which subjects were 
asked questions of the form "Does 
the display contain a T?" (See figure 
6.) Mo